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BEGIN:VEVENT
DTSTART;TZID=UTC:20251101T080000
DTEND;TZID=UTC:20260109T120000
DTSTAMP:20260412T190404
CREATED:20251104T103507Z
LAST-MODIFIED:20260209T165255Z
UID:5847-1761984000-1767960000@aichemy.ac.uk
SUMMARY:Catechol Benchmark Hackathon (NeurIPS 2025 DnB)
DESCRIPTION:ML model-building challenge for reaction yield prediction for catechol rearrangement reaction from transient flow dataset.\n\n\n\n\n\n\n\n\n\n\n\nKEY DETAILS\n\n\n\n\nLAUNCH DATE3rd November 8:00 AM CLOSING DATE9th January 12:00 PM \n\n\n\nVIEW COMPETITION ON kaggle\n\n\n\n\n\n\n\n\nOverview:\n\n\n\nWelcome to the Catechol Benchmark Hackathon competition!  \n\n\n\nIn this competition\, we will have multiple teams trying to prediction reaction outcomes of the rearrangement of allyl substituted catechol under different solvent and process conditions. \n\n\n\nThe data-set consists of multiple transient flow ramps\, which allow us to assess the amount of starting material and products after seeing the reaction at different temperatures and residence times (i.e. how long the chemicals reacted for). We also include many data-points for binary mixtures of solvents\, allowing us to treat the usually discrete solvent selection problem as a semi-continuous one. \n\n\n\nGoal: Build a machine learning model that achieves the best predictions on the collected data\, as measured by a cross-validation procedure\, which will demonstrate the ability of your model to predict on unseen solvent data.  \n\n\n\nDescription\n\n\n\nMore details of the data-set: \n\n\n\nData size and inputs\n\n\n\nThe data-set consists of 1227 data points on the allyl substituted catechol reaction\, covering 24 solvents at different temperatures and residence times. The inputs of the model will consist of: \n\n\n\n(1) A selection of two different solvents\, Solvent A and Solvent B\, with the corresponding amount of Solvent B in the mixture given by the percentage %B. \n\n\n\n(2) The temperature in °C at which the reaction was carried out. \n\n\n\n(3) The residence time of the reaction\, i.e.\, how long the reactants were subject to the reaction conditions applied. \n\n\n\nThe outputs consist of the yield of the starting material and the two observed products. We also created a smaller data set of 656 data-points in which solvent mixtures are not considered\, and only single solvent data\, along with residence times and temperatures is considered. \n\n\n\nEvaluation\n\n\n\nSubmissions will be evaluated according to a cross-validation procedure. This public notebook (https://www.kaggle.com/code/josepablofolch/catechol-benchmark-hackathon-template) shows the structure any submitted notebook must follow. In order to ensure fair participation among all competitors\, the submission must have the same last three cells as in the notebook template\, with the only allowed change being the line where the model is defined.  \n\n\n\nFor the avoidance of doubt\, the line  model = MLPModel() can be replaced with a new model definition in the third to last and second to last cells\, but everything else must remain the same. \n\n\n\nPrizes\n\n\n\nPrizes will be awarded on a per-person basis as follows: \n\n\n\nTotal Prizes Available: £2\,000 (GBP) \n\n\n\n\n1st Place – £250 per person (maximum £1000 total for a team of four)\n\n\n\n2nd Place – £150 per person (maximum £600 total for a team of four)\n\n\n\n3rd Place – £100 per person (maximum £400 total for a team of four)
URL:https://aichemy.ac.uk/event/catechol-benchmark-hackathon-neurips-2025-dnb/
CATEGORIES:Hackathon
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20251208T000000
DTEND;TZID=UTC:20251212T235959
DTSTAMP:20260412T190404
CREATED:20250823T075605Z
LAST-MODIFIED:20260223T111409Z
UID:4377-1765152000-1765583999@aichemy.ac.uk
SUMMARY:Winter School: Robotics and AI for Materials Chemistry 2025
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE8 – 12 December\, 2025 COST£100 \n\n\n\nApplications CLOSED\n\n\n\nView detailed agenda\n\n\n\nRead the Blog\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nChemistry Building\, University of LiverpoolLiverpool\, L69 7ZD\, United Kingdom \n\n\n\n\n\n\n\n\nPlease note: Applications are now closed for this training school. \n\n\n\nThe Robotics and AI for Materials Chemistry Winter School is a five-day intensive training programme focused on digital and automated chemistry\, robotic systems\, and AI-driven scientific discovery. Hosted at the University of Liverpool\, the school is designed for PhD students and early-career researchers\, or those new to digital chemistry and AI\, and who want to build their capabilities in this rapidly evolving field. A strong working knowledge of Python is required to fully benefit from the practical sessions and technical content. \n\n\n\nThis Robotics and AI for Materials Chemistry Winter School will: \n\n\n\n\nProvide essential skills in digital chemistry\n\n\n\nStrengthen understanding of AI and machine learning\, building on participants’ existing knowledge\n\n\n\nOffer hands-on experience with key tools and techniques for automated\, intelligent lab environments\n\n\n\n\nParticipants will explore a range of cutting-edge topics\, including: \n\n\n\n\nDigital twins for robotic chemists\n\n\n\nBayesian optimisation for chemical discovery\n\n\n\nAI-driven robotic chemists\n\n\n\nRobotic manipulation for lab automation\n\n\n\nSimulation of robotic chemists\n\n\n\nComputer vision-led chemistry\n\n\n\nMulti-modal machine learning for science\n\n\n\nAgentic AI-based discovery\n\n\n\nHuman-in-the-loop robotic discovery\n\n\n\n\n\n\n\n\n\nProvisional Programme\n\n\n\nMondayTuesdayWednesdayThursdayFridayInvited Talk: Dr Felix HankeInvited Talk: Dr Michele CaprioPractical Tutorial: Bayesian Optimisation for Chemistry – Dr Bojana RankovicInvited Talk: Dr Efi Psomopoulou Invited Talk: Dr Shijing SunPractical Tutorial: Bayesian Optimisation Basics and Human-in-the-loop modelling’ – Dr Manisha DubeyPractical Tutorial: Robot SimulationPractical Tutorial: Robot ManipulationProject WorkInvited Talk: Prof. Subramanian RamamoorthyPractical Tutorial: Machine Vision for ChemistryProject WorkProject WorkProject WorkProject PresentationsSocial Networking Event\n\n\n\n\n\n\n\nConfirmed Speakers\n\n\n\n\n\nDr Felix HankeCusp AI\n\n\n\n\n\nDr Manisha DubeyUniversity of Edinburgh\n\n\n\n\n\nDr Michele Caprio University of Manchester\n\n\n\n\n\nDr Bojana RankovicEPFL\n\n\n\n\n\n\n\nDr Efi PsomopoulouUniversity of Bristol\n\n\n\n\n\nDr Shijing SunUniversity of Cambridge\n\n\n\n\n\nProf. Subramanian Ramamoorthy University of Edinburgh\n\n\n\n\n\n\n\n\n\nAccommodation and Travel\n\n\n\nPlease note that the registration fee does not include accommodation\, travel or subsistence. Participants are responsible for arranging their own accommodation and transport during the Winter School. \n\n\n\nWe are happy to recommend the Novotel Liverpool Paddington Village\, a modern hotel conveniently located within walking distance of the University of Liverpool campus. This hotel offers comfortable rooms\, breakfast options and easy access to local amenities. \n\n\n\nA social networking event will be hosted on one evening during the school and is included in the registration. \n\n\n\nFor those seeking alternative options\, Liverpool offers a wide range of hotels\, serviced apartments\, and budget accommodations within easy reach of the University. \n\n\n\nLiverpool is well-connected by rail\, with Liverpool Lime Street Station approximately a 10-minute walk from the University campus. For those travelling by car\, parking is available at the Paddington Village Car Park\, located close to the University and the recommended hotel. \n\n\n\nAirports:\n\n\n\n\nLiverpool John Lennon Airport (LPL) – Around 30 minutes from the University by taxi or public transport. The airport offers flights to many UK and European destinations.\n\n\n\nManchester Airport (MAN) – Around 1 hour by train or car\, with direct rail connections to Liverpool Lime Street. This airport provides a wide range of international flight options.\n\n\n\n\n\n\n\n\nHow to Apply:\n\n\n\nPlaces are limited and to ensure a balanced mix of expertise and perspectives we are asking applicants to apply. As demand is expected to be high\, we ask all interested participants to complete the application form by 24th October 2025 and decisions will be given to applicants by 31st October 2025. \n\n\n\nPlease note: all bookings are non-refundable. \n\n\n\n\n\n\n\nContact details:\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk. \n\n\n\n\n\nThe Organising Committee:\n\n\n\nAlchemy HubUniversity of LiverpoolDr. Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Gabriella PizzutoDr Xenofon EvangelopoulosProf. Alessandro TroisiMinh Cao
URL:https://aichemy.ac.uk/event/winter-school-robotics-and-ai-for-materials-chemistry-2025/
CATEGORIES:Training School
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20251210T140000
DTEND;TZID=UTC:20251210T150000
DTSTAMP:20260412T190404
CREATED:20251125T132616Z
LAST-MODIFIED:20260325T135926Z
UID:6325-1765375200-1765378800@aichemy.ac.uk
SUMMARY:AIchemy’s Monthly Webinar Series - December 2025
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE10 December 2025 TIME14:00 – 15:00 COSTFree \n\n\n\n\nRECORDINGSClick the YouTube links below to watch each session. \n\n\n\n\nLarge-scale Crystal Structure Prediction: Learning from 1\,000 molecules and beyond Retention Is All You Get (But Maybe It’s All You Need) \n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nProf. Keith Butler – University College of London \n\n\n\nTalk Title: Retention Is All You Get (But Maybe It’s All You Need): Using Large Language Models to Design and Discover New Materials \n\n\n\nLarge language models (LLMs) have transformed how we work with text\, but their underlying mechanism\, autoregressive next-token prediction\, naturally extends to any domain that can be expressed as a sequence. In this webinar\, Keith will explore how this paradigm can be repurposed for chemistry and materials science by treating crystal structures as a “language” and training LLMs to generate them. \n\n\n\nHe will discuss his recent work developing CrystaLLM\, an autoregressive model trained on large collections of crystallographic data. The model learns the statistical grammar of known materials well enough to generate syntactically valid and chemically plausible crystal structures. However\, detailed interrogation shows that the model’s apparent creativity is predominantly driven by retention\, recombining motifs seen in its training data rather than building a genuine\, generalisable “world model” of chemistry. This distinction is important for how such models are interpreted and deployed in discovery workflows. \n\n\n\nKeith will then introduce his team’s latest extensions using conditional generation\, which allow them to steer the model with property targets or experimental measurements. This approach does not magically endow the model with chemical reasoning\, but it provides a powerful way to exploit its learned structural priors. He will illustrate this with examples such as conditioning on X-ray diffraction patterns to accelerate structure solution and conditioning on target optoelectronic properties to bias generation toward functional materials spaces. \n\n\n\nOverall\, the aim of Keith’s talk is to provide a realistic\, scientifically grounded view of what LLMs can and cannot do for chemical discovery. These models are powerful tools for pattern learning and hypothesis generation\, but they do not yet constitute autonomous scientific reasoners. Understanding this helps researchers design workflows where they offer genuine advantage without overstating their capabilities. \n\n\n\nChris Taylor – University of Southampton \n\n\n\nTalk Title: Large-scale Crystal Structure Prediction: Learning from 1\,000 molecules and beyond \n\n\n\nComputational molecular crystal structure prediction (CSP) is a mature and powerful tool in materials discovery\, able to successfully predict and rank the possible crystal polymorphs of a range of functional materials at increasingly large scale. In this talk\, I describe our landmark study carrying out thorough CSP explorations on over 1\,000 rigid molecules with experimentally-known forms\, demonstrating our CSP workflow’s overwhelming success in predicting and ranking known forms\, and in rationalising empirical crystal engineering rules. I also demonstrate the potential of such large-scale data generation by presenting a machine-learned energy correction and a message-passing (MACE) neural network potential trained on this data\, as examples of the possibilities for employing AI trained on such datasets to empower functional materials discovery. \n\n\n\n\n\nSpeakers\n\n\n\n\n\nProf. Keith ButlerAssociate Professor in Computational Materials Chemistry\n\n\n\n\n\nDr. Chris Taylor Postdoctoral Research Fellow\n\n\n\n\n\nJohn WardWebinar Host
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-december-2025/
CATEGORIES:Webinar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260121T140000
DTEND;TZID=UTC:20260121T150000
DTSTAMP:20260412T190404
CREATED:20251125T150202Z
LAST-MODIFIED:20260128T132906Z
UID:6344-1769004000-1769007600@aichemy.ac.uk
SUMMARY:AIchemy’s Monthly Webinar Series - January 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE21 January 2026 TIME14:00 – 15:00 COSTFree LOCATIONOnline MS Teams \n\n\n\nREGISTRATION CLOSED\n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nAndrea Dimitracopoulos – COO & Co-founder\, Deepmirror \n\n\n\nTalk Title: Tackling Drug Design Challenges with Molecular Assay FingerprintsIn the journey from idea to clinic\, drug discovery teams must balance potency with a wide set of ADMET constraints (solubility\, permeability\, CNS penetration\, clearance\, toxicity risk\, and more). AI can reduce the cost and time of small-molecule drug design by improving both property prediction and molecule prioritisation across the design–make–test–analyse (DMTA) cycle. In this talk\, we introduce molecular assay fingerprints as a learned representation for modelling assay endpoints. This approach combines pre-training on a large assay database with programme-specific fine-tuning to improve prediction accuracy. It also leverages Gaussian processes to quantify predictive uncertainty\, which can then be used to prioritise compounds and explore chemical space efficiently – accelerating programme progression. Benchmarking on private drug programmes illustrates how assay fingerprints can improve predictive accuracy for both potency and key ADMET properties\, dramatically reducing the number of design cycles. \n\n\n\nFederico Ottomano – Imperial College LondonTalk Title: Scalable molecular elucidation from IR and NMR spectroscopy using Machine Learning \n\n\n\n\n\nSpeakers\n\n\n\n\n\nAndrea DimitracopoulosCOO & Co-founder\, Deepmirror\n\n\n\n\n\nFederico Ottomano Postdoctoral Research Assistant\, Imperial College London\n\n\n\n\n\nGabriella Pizzuto – Webinar ChairLecturer (Assistant Professor)
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-january-2026/
CATEGORIES:Webinar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260127T090000
DTEND;TZID=UTC:20260127T170000
DTSTAMP:20260412T190404
CREATED:20250929T131708Z
LAST-MODIFIED:20260223T111247Z
UID:5257-1769504400-1769533200@aichemy.ac.uk
SUMMARY:New Starters in AI for Chemistry
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE27 January 2026 TIME09:00 – 17:00 COSTFREE REGISTRATION DEADLINE23rd January 2026 \n\n\n\nView Agenda\n\n\n\nread the highlights blog\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUNIVERSITY OF LEEDSCLOTH HALL COURT\, QUEBEC ST\, LS1 2HA \n\n\n\n\n\n\n\n\nJoin us for a one day Symposium at Cloth Hall Court\, University of Leeds where we aim to bring together recently appointed academics\, postdoctoral researchers and late-stage PhD students who are developing and deploying AI at the chemistry interface.We welcome researchers from all backgrounds across the physical sciences. Our aim is to build a supportive and inclusive community where you can learn\, share experiences\, and explore topical areas such as molecular and materials design\, generative models\, robotics and automation for autonomous experimentation\, data-driven simulation\, and green and sustainable chemistry.AI and ML is opening new frontiers across the chemical sciences from accelerating materials discovery\, to enabling sustainable reactions and autonomous experimentation. If you’re ready to join the community\, and be part of shaping the future of AI in chemistry\, this is the place to begin.  \n\n\n\n\n\n\n\nWho Should Attend: \n\n\n\nThe event will be open to all but is ideally suited to academic staff\, postdoctoral researchers and PhD students from a range of backgrounds and operating at the AI for Chemistry interface.Early-career academics are encouraged to submit applications for oral presentations.Postdoctoral researchers are encouraged to submit applications for an oral presentation or a poster presentation\, depending on the stage of the work that will be presented..PhD students are encouraged to submit applications for poster presentations. \n\n\n\n\n\nConfirmed Speakers\n\n\n\n\n\nDr Gabriella PizzutoUniversity of Liverpool\n\n\n\n\n\nDr Sam Parkinson Aston University\n\n\n\n\n\nDr Emma King-Smith University of Edinburgh\n\n\n\n\n\nDr Michael TilbyUniversity of Bristol\n\n\n\n\n\n\n\nDr Angelo FreiUniversity of York\n\n\n\n\n\nDr Xenfon EvangelopoulosUniversity of Liverpool\n\n\n\n\n\nDr Joe Marsden University of Leeds\n\n\n\n\n\nDr Elenora RicciUniversity of Edinburgh\n\n\n\n\n\nDr William RobinsonRadboud University\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk. \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubUniversity of LeedsDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Adam ClaytonDr Gilian Thomas
URL:https://aichemy.ac.uk/event/new-starters-in-ai-for-chemistry/
CATEGORIES:Symposium
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260218T140000
DTEND;TZID=UTC:20260218T150000
DTSTAMP:20260412T190404
CREATED:20260128T132849Z
LAST-MODIFIED:20260325T134403Z
UID:6631-1771423200-1771426800@aichemy.ac.uk
SUMMARY:AIchemy’s Monthly Webinar Series - February 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE18 February 2026 TIME14:00 – 15:00 COSTFree LOCATIONOnline MS Teams \n\n\n\n\nRECORDINGSClick the YouTube links below to watch each session. \n\n\n\n\nOrganometallic Chemistry x Data Science Rethinking Generative AI for Materials Discovery \n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nProf. Natalie Fey – University of Bristol \n\n\n\nTalk Title: Organometallic Chemistry x Data ScienceComputational studies of homogeneous catalysis play an increasingly important role in furthering (and changing) our understanding of catalytic cycles and can help to guide the discovery and evaluation of new organometallic catalysts. While a truly “rational design” process often remains out of reach\, detailed mechanistic information from both experiment and computation can be combined successfully with suitable parameters characterising catalysts and substrates to predict outcomes and guide screening. \n\n\n\nIn this presentation\, I will use examples drawn from our recent work\, including the exploration of maps of chemical space and of a reactivity database\, to illustrate how we are increasingly applying data science techniques for visualisation and prediction\, with the goal of informing the discovery and design of suitable organometallic catalysts. \n\n\n\nHyunsoo Park – Imperial College LondonTalk Title: Rethinking Generative AI for Materials Discovery \n\n\n\nGenerative artificial intelligence (AI) has emerged as a potent paradigm for inverse materials design\, offering the potential to invert traditional discovery workflows by directly proposing structures that satisfy desired properties. However\, a fundamental challenge persists regarding the standard training objectives used in generative AI versus the goals of materials discovery. A critical misalignment exists between the likelihood-based sampling typical of generative modelling and the targeted focus on underexplored regions required to identify novel compounds. \n\n\n\nTo address this challenge\, this talk presents Chemeleon2\, a framework that reformulates crystal generation as a reinforcement learning (RL) task. Through the integration of Group Relative Policy Optimization (GRPO) with latent diffusion models\, the system optimizes multi-objective rewards to simultaneously achieve stability\, diversity\, and novelty. The presentation further details how this methodology facilitates property-guided design\, ensuring chemical validity while isolating desired functionalities. Ultimately\, this approach establishes a modular foundation for controllable\, AI-driven inverse design\, effectively addressing the novelty-validity trade-off inherent in scientific discovery applications. \n\n\n\n\n\nSpeakers\n\n\n\n\n\nProf. Natalie FeyProfessor of Chemistry\n\n\n\n\n\nHyunsoo Park Research Associate in Materials Informatics\n\n\n\n\n\nDr. Adam ClaytonWebinar HostAssociate Professor
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-february-2026/
CATEGORIES:Webinar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260311T000000
DTEND;TZID=UTC:20260415T235959
DTSTAMP:20260412T190404
CREATED:20260209T105627Z
LAST-MODIFIED:20260209T110744Z
UID:7430-1773187200-1776297599@aichemy.ac.uk
SUMMARY:Patenting AI & Materials: IP Webinars
DESCRIPTION:KEY DETAILS\n\n\n\n\nWEBINAR 1: IP FUNDAMENTALS DATE & TIME11 march 2026\, 14:00 – 15:00 WEBINAR 2: STRATEGIC IP DATE & TIME15 APRIL 2026\, 14:00 – 15:00 \n\n\n\nWEBINAR 1 Register HERE\n\n\n\nWEBINAR 2 Register HERE\n\n\n\n\n\n\n\n\nJoin Keltie LLP patent attorneys Dr Monica Patel and Dr Emily Weal for a two-part webinar series on protecting innovation at the intersection of AI and materials science. The sessions will guide researchers\, innovators and start-ups through IP fundamentals\, patenting strategies\, and practical tools for recognising and protecting commercially valuable ideas in AI-enabled materials discovery. \n\n\n\nWEBINAR 1: IP FUNDAMENTALS \n\n\n\nThis webinar will introduce the fundamentals of IP for researchers and innovators working at the intersection of AI and materials. The session will cover the differences between patents\, registered designs and trade marks\, how the patent process works in the UK and internationally\, and what typical hurdles to patentability look like in practice. The session will showcase real examples of patentable technologies in materials science and AI\, and highlight how AI-driven approaches are being applied to materials discovery and development. The webinar is designed for a broad audience\, and no prior knowledge of IP or patents is required. \n\n\n\nWEBINAR 2: STRATEGIC IP \n\n\n\nThis webinar will build on these foundations to focus on how to recognise and protect commercially valuable ideas in AI and materials. The session will cover how to identify patentable inventions in your research\, principles of strategic patent drafting for data-driven and AI-enabled materials innovations\, and common IP ownership and collaboration pitfalls in multi-partner projects. The session will also cover an introduction to competitor patent searching and patent landscaping techniques\, and practical IP tips tailored for start-ups and spin-outs emerging from the AI and materials ecosystem. While open to all\, attendees will benefit from having joined Webinar 1 or having a basic familiarity with core IP concepts. \n\n\n\n\n\nSpeakers\n\n\n\n\n\nDr Monica PatelSenior Associate\, Keltie LLP\n\n\n\n\n\nDr Emily WealPartner\, Keltie LLP
URL:https://aichemy.ac.uk/event/patenting-ai-materials-ip-webinars-keltiellp/
CATEGORIES:Webinar
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260318T140000
DTEND;TZID=UTC:20260318T150000
DTSTAMP:20260412T190404
CREATED:20260209T224922Z
LAST-MODIFIED:20260325T144026Z
UID:7477-1773842400-1773846000@aichemy.ac.uk
SUMMARY:AIchemy’s Monthly Webinar Series – March 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE18 March 2026 TIME14:00 – 15:00 COSTFree LOCATIONOnline MS Teams \n\n\n\n\nRECORDINGSClick the YouTube links below to watch each session. \n\n\n\n\nResolving the data ambiguity for periodic crystals The Crystal Geomap visualises materials databases in real time. \n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nProf. Vitaliy Kurlin – University of Liverpool \n\n\n\nTalk Title: Resolving the data ambiguity for periodic crystalsThe discontinuity of cell-based representations of periodic crystals under almost any noise has been known theoretically and experimentally at least since 1965. As a result\, major materials databases accumulated thousands of near-duplicate structures that could not be recognized by any past tools [1]. The latest example is the correction of the A-lab paper in Nature [2]\, where almost all words “novel” and “discovery” were crossed out. We will present a rigorously justified approach to uniquely identifying the atomic structure of any periodic crystal by complete\, continuous and fast geometric codes [3]. \n\n\n\n[1] D.Chawla. C&EN news\, https://cen.acs.org/research-integrity/Duplicate-structures-haunt-crystallography-databases/103/web/2025/12. \n\n\n\n[2] N.Szymanski et al. Author Correction: An autonomous laboratory for the accelerated synthesis of inorganic materials. Nature (2026)\, https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-025-09992-y/MediaObjects/41586_2025_9992_MOESM1_ESM.pdf \n\n\n\n[3] D.Widdowson\, V.Kurlin. Resolving the data ambiguity for periodic crystals. NeurIPS 2022\, v.35\, p.24625-2463. Extended version to appear in SIAM J Appl. Math. 2026\, https://arxiv.org/abs/2108.04798. \n\n\n\nDr. Daniel Widdowson  – University of Liverpool \n\n\n\nTalk Title: The Crystal Geomap visualises materials databases in real time \n\n\n\nOur rigorously justified invariants of crystals give rise to a continuous space containing all crystals\, where the proximity of two crystals does not depend on a choice of unit cell and motif\, but whether the two structures can be closely matched atom for atom by isometry [4]. This led us to develop software to visualise this space and be an interface to ultra-fast comparisons of crystals enabled by our invariants [5]. In this talk we will explore unusual “features” of crystal databases such as the ICSD made visible by our depictions of crystal space\, examples of nearly identical crystals represented with completely different cells and motifs [6]\, and a live example of detection of all geometric (near-)duplicates in the ICSD\, a calculation which was computationally intractable by existing methods. \n\n\n\n[4] O.Anosova\, V.Kurlin\, M.Senechal. The importance of definitions in crystallography. IUCrJ\, v.11(4)\, p.453-463 (2024). \n\n\n\n[5] D.Widdowson\, V.Kurlin. Continuous invariant-based maps of the Cambridge Structural Database. Crystal Growth & Design\, v.24(13)\, p.5627–5636 (2024). \n\n\n\n[6] D.Widdowson\, V.Kurlin. Geographic-style maps with a local novelty distance help navigate the materials space. Scientific Reports\, v.15\, 27588 (2025). \n\n\n\n\n\nSpeakers\n\n\n\n\n\nProf. Vitaliy KurlinProfessor of Computer Science\n\n\n\n\n\nDr. Daniel Widdowson Senior Software Engineer\n\n\n\n\n\nDr. John Ward – Webinar Chair Lecturer in Chemistry
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-march-2026/
CATEGORIES:Webinar
ATTACH;FMTTYPE=image/png:https://aichemy.ac.uk/wp-content/uploads/2026/02/Aichemy-Webinar-Mar-2026.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260327T090000
DTEND;TZID=UTC:20260327T170000
DTSTAMP:20260412T190404
CREATED:20260109T124118Z
LAST-MODIFIED:20260122T101757Z
UID:6501-1774602000-1774630800@aichemy.ac.uk
SUMMARY:Generative Modeling Spring School 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE23rd March 2026 – 27th March 2026 COST£400 – £1000* – further details on GEMSS website APPLICATION DEADLINE23rd January 11:59pm \n\n\n\nmore info & to apply click Here\n\n\n\n\n\n\nVENUE LOCATION\n\n\n\n\nImperial College London Monday to Wednesday at the South Kensington Campus Exhibition Road\, London SW7 2AZ. Thursday and Friday at White City CampusMolecular Sciences Research Hub\, White City\, London W12 0BZ. \n\n\n\n\n\n\n\n\nDescription\n\n\n\nThe AIchemy Hub is pleased to sponsor and co-host the Generative Modelling Spring School (GEMSS) 2026 at Imperial College.GeMSS is a European spring/summer school dedicated exclusively to deep generative models\, including latent variable models\, diffusion and flow-based models\, and autoregressive generative models. It primarily attracts PhD students and researchers across Europe with an interest in generative modeling. \n\n\n\nThe school has a distinctive format: the first three days focus on intensive lectures and tutorials covering foundational concepts\, followed by invited talks on state-of-the-art generative models that highlight current research frontiers. \n\n\n\nGeMSS is aimed at PhD students working broadly in data science and AI for whom generative modeling is\, or may become\, an important component of their research. The program is designed to be relevant both for students pursuing methodological research (e.g.\, machine learning\, statistics\, and AI) and for those working in applied domains such as bioinformatics\, computational physics\, computational chemistry\, and computational social science. The school is also open to postdocs and senior researchers from academia and industry as part of their continuing training in generative AI. \n\n\n\nSubmission & Registration\n\n\n\nFull details on the application and selection process is available on the GeMSS website. \n\n\n\n\n\nLecturers\n\n\n\nThe first three days will be taught by the main lectures\, while there will be invited lectures giving tutorials the last two days.  \n\n\n\n\nJoey Bose\, Imperial College London\n\n\n\nAlbert Q. Jiang\, Mistral AI\n\n\n\nSimon Olsson\, Chalmers University of Technology\n\n\n\nArnaud Doucet\, University of Oxford & DeepMind\n\n\n\nJakub M. Tomczak\, Chan Zuckerberg Initiative\n\n\n\nPierre-Alexandre Mattei\, Inria\, Université Côte d’Azur\n\n\n\nJes Frellsen\, Technical University of Denmark\n\n\n\n\n\n\nOrganisation & Sponsors\n\n\n\nThe summer school is jointly organised by: \n\n\n\n\nYingzhen Li\, Imperial College London)\n\n\n\nBenjamin Guedj\, University College London\, Inria\n\n\n\nPierre-Alexandre Mattei\, Inria\, Université Côte d’Azur\n\n\n\nJakub M. Tomczak\, Chan Zuckerberg Initiative\n\n\n\nJes Frellsen\, Technical University of Denmark\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nContact\n\n\n\nFor matters regarding the summer school\, please contact gemss@sciencesconf.org. \n\n\n\n\n\n\n\n\n\n\n\nOutline Agenda – Draft\n\n\n\nThe full agenda is on the GeMSS website. \n\n\n\n\n\n\n\nMonday (Mar 23)South KensingtonTuesday (Mar 24)South KensingtonWednesday (Mar 25)South KensingtonThursday (Mar 26)White CityFriday (Mar 27)White City9:00-9:15Opening remarks9:15-10:30Lecture9:30-10:30Lecture9:30-10:30Lecture09:00-10:30Invited talk09:00-10:30Invited talk11:00-12:00Lecture11:00-12:00Lecture11:00-12:00Lecture11:00-12:30Invited talk11:00-12:30Invited talk12:00-13:30Lunch12:00-13:30Lunch12:00-13:30Lunch12:30-14:00Lunch12:30-14:00Lunch13:30-15:00Lecture13:30-15:00Lecture13:30-15:00Lecture14:00-15:30Invited talk14:00-15:30Invited talk15:30-17:00Lecture15:30-16:30Lecture15:30-16:30Lecture16:00-17:30Invited talk16:00-16.30Closing17:15-18:30Hands-on session17:00-18:30Hands-on session17:00-19:00Poster session19:00Gala dinner
URL:https://aichemy.ac.uk/event/generative-modeling-spring-school-2026/
CATEGORIES:Training School
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260402T100000
DTEND;TZID=UTC:20260402T170000
DTSTAMP:20260412T190404
CREATED:20260120T173007Z
LAST-MODIFIED:20260407T060313Z
UID:6577-1775124000-1775149200@aichemy.ac.uk
SUMMARY:Machine Learning for Experimental Materials Data
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE2nd April 2026 TIME10:00 – 17:00 Registration fee£0 – IOP & Associate Member      £15 – Student Non-Member £30 – Non-Member Registration Deadline20th March 2026 \n\n\n\nRegisteration now closed\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\ninstitute of physics37 Caledonian Rd\, London N1 9BU \n\n\n\n\n\n\n\n\nPlease note: This Event has now passed \n\n\n\nJoin our IOP–AIchemy co-sponsored mini-symposium on machine learning for experimental materials data. This event will unite experimentalists and computational scientists to identify shared challenges\, exchange practical solutions\, and showcase how ML accelerates analysis across scattering\, microscopy\, tomography\, and spectroscopy; driving faster\, more insightful materials discovery. \n\n\n\nThis event is open to everyone\, whatever your background — whether you’re a practising physicist or simply curious to explore the subject. \n\n\n\n\n\nSpeakers:\n\n\n\n\nSam Cooper\, Imperial College London\n\n\n\nKim Jelfs\, Imperial College London\n\n\n\nAndrew McClusky\, University of Bristol\n\n\n\nDylan Owen\, University of Birmingham\n\n\n\nRob Palgrave\, University College London\n\n\n\nShijing Sun\, University of Cambridge\n\n\n\nSarah Haigh\, University of Manchester\n\n\n\nShelley Conroy\, Imperial College London \n\n\n\n\n\n\nPoster Abstracts \n\n\n\nWe invite contributions for poster presentations. If you are interested in presenting a poster\, please submit a short abstract (max 250 words) by email to claire.garland@iop.org by 20 March 2026. Posters will be A0 in portrait orientation. \n\n\n\n\n\nOrganised by:\n\n\n\n\nKelvin Wong\, Post Graduate Teaching Assistant – University College London\n\n\n\nKeith Butler\, Associate Professor in Computational Materials Chemistry – University College London\n\n\n\nAron Walsh – Professor at Imperial College & CSO at CuspAI
URL:https://aichemy.ac.uk/event/machine-learning-for-experimental-materials-data/
CATEGORIES:Symposium,Workshop
ATTACH;FMTTYPE=image/png:https://aichemy.ac.uk/wp-content/uploads/2026/01/Machine-Learning-for-Experimental-Materials-Data-ft-image-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260413T000000
DTEND;TZID=UTC:20260417T235959
DTSTAMP:20260412T190404
CREATED:20251027T135314Z
LAST-MODIFIED:20251114T123044Z
UID:5736-1776038400-1776470399@aichemy.ac.uk
SUMMARY:CaMMLs - Chemical and materials machine learning school 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE & TIME13th April – 17th April 2026 COST£250 APPLICATION DEADLINE26th November 2025 \n\n\n\napply Here\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nSTFC Daresbury LabKeckwick Ln\, Daresbury\, Warrington WA4 4AD \n\n\n\n\n\n\n\n\nDescription\n\n\n\nThis machine learning for materials training course is being run by AIchemy Hub in collaboration with Physical Sciences Data Infrastructure (PSDI) initiative with support from STFC-SCD\, PSDS\, CCP5 and CCP9. This training is targeted towards PhD students\, in particular those in the Materials and Molecular Simulations field\, who have experience of coding but are not highly experienced with machine learning. The aim of this training is to introduce attendees to the latest methods of machine learning for the atomistic simulation of materials. \n\n\n\nThis training will encompass a number of talks and practical sessions\, focusing on the basics of machine learning\, machine learning interatomic potentials and graph neural networks. There will also be the opportunity for attendees to present a poster on their work. \n\n\n\nLearning outcomes\n\n\n\n\nAwareness of the state-of-the-art methods for machine learning for atomistic and molecular simulations\n\n\n\nHands on experience of using machine learning for atomistic and molecular simulations\n\n\n\n\nOutline Agenda – Draft\n\n\n\nSessionsMondayTuesdayWednesdayThursdayFridayMorning  DescriptorsNNsMLIPs generalGenerative modelsAfternoonIntro to MLBayesian OptimisationGNNsMLIPs – molecules/ materials EveningPostersResearch Seminar – Ruby Sedgwick – XymeBBQResearch Seminar – Venkat Kapil – UCL \n\n\n\nPre-requisites\n\n\n\nStudents attending this course must already have a foundational level of Python experience and hands on experience of using Python in their research. You will be expected to provide your own laptop for the training course\, although software installation will not be required. A letter of support will be required from your supervisor alongside your application\, this will be requested by email following your application. This letter of support is to show the backing of your supervisor to attend the training and must be completed for your application to be assessed.  \n\n\n\nTimelines & Fees\n\n\n\nThe application deadline is 26th November 2025. Supervisors will be contacted for a letter of support following you application. All letters of support must be submitted by 6th December 2025. \n\n\n\nYou will be informed of the outcome of your application on 19th December 2025\, you will have to accept your place by 15th January 2026 and payment is required by 13th February 2026.  \n\n\n\nFood and 4 nights accommodation (Travelodge Warrington) is included in the £250 fee paid for this event\, travel to Daresbury (and public transport to /from the lab) is not included and will need to be covered by the attendee.  \n\n\n\nPlease note: places on this course are limited and in the event of oversubscription to the training course we will favour a diverse group of attendees.   \n\n\n\n\n\nThe Organising Committee:\n\n\n\nAlchemy HubCaMMLSDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr. Chris Mellor (Imperial)Aysel Sarzosa Llerena (Imperial)Alin-Marin Elena (Scientific Computing Department\, STFC) Keith Butler (University College London)Reinhard Maurer (University of Vienna)Alex Ganose (Imperial)Ioan-Bogdan Magdău (Newcastle University)Nicola Knight (University of Southampton)
URL:https://aichemy.ac.uk/event/cammls-chemical-and-materials-machine-learning-school-2026/
CATEGORIES:Training School
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260422T140000
DTEND;TZID=UTC:20260422T150000
DTSTAMP:20260412T190404
CREATED:20260325T142551Z
LAST-MODIFIED:20260327T100048Z
UID:8490-1776866400-1776870000@aichemy.ac.uk
SUMMARY:AIchemy’s Monthly Webinar Series – April 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE22nd April 2026 TIME14:00 – 15:00 COSTFree LOCATIONOnline MS Teams \n\n\n\nREGISTER HERE\n\n\n\n\n\n\n\n\nWe are delighted to welcome you to our AIchemy Hub’s monthly webinar series. \n\n\n\nThis month’s talks: \n\n\n\nProf. Lilo D. Pozzo – University of Washington \n\n\n\nTalk Title: AI-Driven Experiments and Open-Source Automation for Accelerated Soft Matter Research \n\n\n\nArtificial intelligence (AI)\, when paired with accessible laboratory automation\, can greatly accelerate materials optimization and scientific discovery. For example\, it can be used to efficiently map a phase-diagram with intelligent sampling along phase boundaries\, or in ‘retrosynthesis’ problems where a material with a target structure is desired but a synthetic route is not known. These approaches are especially promising in soft matter systems\, including block copolymer self-assembly\, nanoparticle synthesis\, and controlled colloidal assembly. In these systems\, design parameters (e.g. chemical composition\, MW\, topology\, processing) are vast\, history-dependent metastable and ‘out-of-equilibrium’ structures are common\, and functional properties are intimately tied to molecular design features and processing conditions. In addition\, for AI algorithms to operate efficiently in these spaces\, they must be ‘encoded’ with domain expertise specific to the problems being tackled. This talk will cover recent advances in accelerated materials research involving polymeric and soft-matter systems including dispersions and colloids. It will also outline remaining challenges and future opportunities. \n\n\n\nShort Biosketch: \n\n\n\nProf. Pozzo’s research interests are in the area of colloids\, polymers and soft-matter systems. Her research group focuses on controlling and manipulating materials structure for applications in healthcare\, alternative energy and sustainability. Her group also develops and utilizes laboratory automation and artificial intelligence (AI) to accelerate the development time-scales of new materials and applies advanced techniques based on neutron and x-ray scattering to characterize their nanostructure. Prof. Pozzo obtained her B.S. from the University of Puerto Rico at Mayagüez and her PhD in Chemical Engineering from Carnegie Mellon University in Pittsburgh PA. She also worked at the NIST Center for Neutron Research as a post-doctoral fellow and is currently the Boeing-Roundhill Chair Professor of Chemical Engineering at the University of Washington where she has served since 2007. She has been recognized with awards such as the Early Career Award from the Department of Energy\, the Clean Energy Empowerment and Education Award (C3E) from DOE\, and the Anne Mayes Award from the Neutron Scattering Society of America (NSSA). In addition to her research activities\, she is also dedicated to improving engineering education with course development in areas of entrepreneurship and service-oriented global engagement. \n\n\n\nJiyizhe Zhang – The University of Manchester \n\n\n\nTalk Title: Developing sustainable separation processes with AI \n\n\n\nChemical separations have long been essential to human society\, yet the separation of complex mixtures often remains lengthy and costly. Liquid-liquid extraction\, as a separation technology\, has wide applications in pharmaceuticals\, bioprocessing\, critical mineral recovery\, and nuclear waste treatment. Despite its widespread use\, many of the underlying physicochemical phenomena in liquid-liquid systems are not fully understood\, and the process development still relies heavily on shake-flask experiments as decades ago. This talk will present emerging technologies to accelerate separation process development through artificial intelligence\, automation\, and process modelling. Key challenges and future opportunities for digitalising separation science will be discussed. \n\n\n\n\n\nSpeakers\n\n\n\n\n\nProf. Lilo D. Pozzo Professor of Chemical Engineering\n\n\n\n\n\nJiyizhe Zhang Lecturer in Chemical Engineering\n\n\n\n\n\nTahereh Nematiaram – Webinar Chair Chancellor’s Fellow
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-april-2026/
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BEGIN:VEVENT
DTSTART;TZID=UTC:20260513T090000
DTEND;TZID=UTC:20260513T180000
DTSTAMP:20260412T190404
CREATED:20260211T154100Z
LAST-MODIFIED:20260216T094635Z
UID:7352-1778662800-1778695200@aichemy.ac.uk
SUMMARY:Applications of AI for Catalysis and Energy Materials Discovery
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE13th May 2026 TIME09:00 – 18:00 COST£25* Registration fee may be covered if required\, please contact us.   \n\n\n\nbook now\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nMolecular Sciences Research Hub (MSRH)\,  Imperial College London82 Wood Ln\, London W12 0BZ \n\n\n\n\n\n\n\n\nJoin us for a one-day symposium bringing together researchers working in catalysis and energy materials with AI experts developing and applying machine learning methods in this space.  \n\n\n\nThe programme features talks from leading researchers across chemistry\, materials science\, and AI\, showcasing real-world applications of data-driven approaches in catalysis\, interfaces\, electrolytes\, membranes\, and energy materials. \n\n\n\nThe day will combine invited talks\, discussion\, and dedicated networking time\, providing opportunities to share ideas\, learn about emerging methods\, and spark new interdisciplinary collaborations across experimental\, computational and machine learning research in the area of catalysis and energy materials. \n\n\n\nWho Should Attend:\n\n\n\nThis symposium is designed for: \n\n\n\n\nAcademics and researchers in catalysis\, interfaces\, and energy materials who are interested in applying AI and machine learning to enhance\, accelerate\, or expand their research.\n\n\n\nAI and machine learning experts looking to apply novel computational approaches to challenges in catalysis\, reaction engineering\, molecular discovery\, and energy‑relevant materials.\n\n\n\n\nWhether your work is experimental\, theoretical\, computational\, or method‑development‑focused\, this event offers a unique opportunity to build connections across disciplines and gain insights into the rapidly evolving intersection of AI\, catalysis\, and materials discovery. \n\n\n\nFull Agenda coming soon. \n\n\n\n\n\nSpeakers:\n\n\n\n\nProf. Evgeny Pidko – Delft University of Technology (TU Delft)\n\n\n\nProf. Fernanda Duarte – University of Oxford\, Department of Chemistry\n\n\n\nProf. Jacqui Cole – University of Cambridge\n\n\n\nDr. James Dawson – Newcastle University\n\n\n\nProf. James Durrant – University of Oxford\n\n\n\nProf. Maria Lukatskaya – ETH Zürich\n\n\n\nDr. Ricardo Grau‑Crespo – Queen Mary University of London\n\n\n\nDr. Qilei Song – Imperial College London\n\n\n\n\n\n\nRegistration Fee:\n\n\n\nIf the registration fee would otherwise prevent you from attending\, please don’t let this deter you\, just get in touch with us to discuss support. Contact details:Aysel Sarzosa (asarzosa@ic.ac.uk) or Chris Mellor (c.mellor@imperial.ac.uk). \n\n\n\nIn addition\, if you have caring responsibilities that may affect your ability to attend\, take a look at our Conference Care Fund and get in touch to see how we can support you to attend. \n\n\n\n\n\n\n\n\n\nOrganised by:\n\n\n\nDr Maryam Mansoori Kermani\, MSCA Fellow at Imperial College London with the support of AIchemy Hub – Project Team.
URL:https://aichemy.ac.uk/event/applications-of-ai-for-catalysis-and-energy-materials-discovery/
CATEGORIES:Symposium,Workshop
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260602T090000
DTEND;TZID=UTC:20260602T170000
DTSTAMP:20260412T190404
CREATED:20260220T114907Z
LAST-MODIFIED:20260224T133917Z
UID:7844-1780390800-1780419600@aichemy.ac.uk
SUMMARY:ECR Exchange: Scotland 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE2 JUNE 2026 TIME09:00 – 17:00 COSTFREE ABSTRACT SUBMISSION DEADLINE27 APRIL 2026 REGISTRATION DEADLINE12 MAY 2026 \n\n\n\nbook now\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUNIVERSITY OF STRATHCLYDETechnology and Innovation Centre\, 99 George Street\,  Glasgow\, G1 1RD \n\n\n\n\n\n\n\n\nThe AIchemy ECR Exchange is primarily aimed at Early Career Researchers across the UK\, including PhD students and postdoctoral researchers working at the intersection of AI and Chemistry. While Scotland-focused\, the event welcomes participants from further afield who are keen to contribute to and engage with a growing research community. This Exchange is designed to connect emerging researchers\, create space for meaningful networking\, and encourage open knowledge sharing. By bringing together ECRs working across disciplines\, the event aims to spark new collaborations and lay the groundwork for future collaboration opportunities.Through engagement with industry speakers and partners\, attendees will gain insight into real-world challenges and translational pathways\, helping to shape and focus their research and future career development. \n\n\n\n\n\n\n\nCall for Lightning Talk Abstracts \n\n\n\nWe invite submissions of oral and poster abstracts from researchers working across all areas at the intersection of AI and Chemistry\, including interdisciplinary and applied research. This is an opportunity for ECR’s\, PhD students and postdoctoral researchers to showcase their work to a focused audience of peers\, academic leaders\, and industry representatives working at the AI and chemistry interface. Selected applicants will be invited to deliver an oral presentation as part of the main programme\, providing a platform to share their research\, receive feedback\, and spark potential collaborations. There will also be the opportunity to present a poster\, creating additional space for discussion\, networking\, and deeper engagement with attendees. Abstract submission deadline: 27th April \n\n\n\n\n\n\n\nWho Should Attend: \n\n\n\nThe AIchemy ECR Exchange is primarily aimed at Early Career Researchers\, including: \n\n\n\n\nPhD students\n\n\n\nPostdoctoral researchers\n\n\n\nEarly Career Independent Academic\n\n\n\n\nThe event is relevant but not limited to those interested in the application or development of AI for accelerated chemistry and materials discovery. Participation is open to researchers from across the UK who are keen to collaborate and engage with Scotland’s research community. \n\n\n\nWhat you’ll gain: \n\n\n\n\nOpportunities to present and discuss their research\n\n\n\nDedicated networking to encourage future collaborations\n\n\n\nInsight from industry speakers on real-world challenges\n\n\n\nExposure to potential pathways for research impact and funding\n\n\n\n\n\n\nSpeakers– To be Announced\n\n\n\n\n\n\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubUniversity of StrathclydeDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Tahereh NematiaramDr Yashar Moshfeghi
URL:https://aichemy.ac.uk/event/ecr-exchange-scotland-2026/
CATEGORIES:Symposium
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=UTC:20260618T170000
DTEND;TZID=UTC:20260618T210000
DTSTAMP:20260412T190404
CREATED:20260407T072353Z
LAST-MODIFIED:20260407T072355Z
UID:8110-1781802000-1781816400@aichemy.ac.uk
SUMMARY:Science in the City: An Evening of AI
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE18 JUNE 2026 TIME17:00 – 21:00 COSTFREE \n\n\n\nbook now\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nTHE SPINE BUILDING2 Paddington Village\, Liverpool L7 3FA \n\n\n\n\n\n\n\n\nStep into the world of AI and see how it’s shaping science\, healthcare\, and innovation across Liverpool and the UK. From groundbreaking research at the University of Liverpool to real-world applications in our city region\, this event brings science to life for a community that takes pride in Liverpool’s innovation\, collaboration\, and world-class research. Meet researchers and take part in discussions with experts\, ask your questions\, share your ideas\, and see how AI is being used responsibly to make a positive impact. This event is open to everyone\, whether you’re a researcher\, city resident\, alumni or just curious about how AI is shaping the future. Enjoy a welcoming reception before and after the event\, the perfect time to meet fellow attendees\, spark conversations\, and celebrate Liverpool’s thriving research community.Please Note: Registration to this event is essential \n\n\n\n\n\n\n\nWhat you’ll gain: \n\n\n\n\nExplore how AI is driving breakthroughs in science.\n\n\n\nEngage directly with experts in Q&A sessions.\n\n\n\nCelebrate and support our city’s research excellence.\n\n\n\n\nNo prior experience in AI is required\, just curiosity and a desire to be part of the talent\, dedication\, and pride that Liverpool brings to the forefront of scientific discovery. \n\n\n\n\n\n\n\nEvening Programme: \n\n\n\n5:00 – 6:00pm | Arrival & Welcome ReceptionJoin us for a relaxed welcome with refreshments. Meet fellow attendees and start the conversation in an informal setting overlooking Liverpool’s vibrant skyline.6:00 – 8:00pm | AI Across the Sciences – Speaker Sessions & DiscussionHear from leading voices in AI and scientific research as they explore how artificial intelligence is advancing materials chemistry\, drug discovery\, healthcare\, and more. Each session will include opportunities for questions and audience interaction.8:00 – 9:00pm | Conversations & Community ReceptionContinue the discussion over refreshments. Connect with researchers\, alumni\, and partners\, and be part of the growing AI and science community shaping Liverpool’s future. \n\n\n\n\n\nSpeakers\n\n\n\n\n\nProfessor Andy CooperUniversity of Liverpool\n\n\n\n\n\nProfessor Katie AtkinsonUniversity of Liverpool\n\n\n\n\n\nDr Alex BattyClatterbridge Cancer Centre\n\n\n\n\n\nDr Gabriella PizzutoUniversity of Liverpool\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nAccommodation and Travel\n\n\n\nWe are happy to recommend the Novotel Liverpool Paddington Village\, a modern hotel conveniently located within walking distance of the University of Liverpool campus. This hotel offers comfortable rooms\, breakfast options and easy access to local amenities. \n\n\n\nLiverpool is well-connected by rail\, with Liverpool Lime Street Station approximately a 10-minute walk from the University campus. For those travelling by car\, parking is available at the Paddington Village Car Park\, located close to the University\, The Spine Building and the recommended hotel. \n\n\n\n\n\n\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)
URL:https://aichemy.ac.uk/event/science-in-the-city-an-evening-of-ai/
CATEGORIES:Symposium
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DTSTART;TZID=UTC:20260721T090000
DTEND;TZID=UTC:20260721T170000
DTSTAMP:20260412T190404
CREATED:20260206T072607Z
LAST-MODIFIED:20260211T131150Z
UID:7121-1784624400-1784653200@aichemy.ac.uk
SUMMARY:Gen AI In Chemistry Education
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE21 JULY 2026 TIME09:00 – 17:00 COST£25 LIGHTNING TALK SUBMISSION DEADLINE1 MAY 2026 REGISTRATION DEADLINE3 JULY 2026 \n\n\n\nREGISTration Open\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUNIVERSITY OF LIVERPOOLCentral Teaching Labs \n\n\n\n\n\n\n\n\nThis UK national symposium brings together chemistry educators\, students\, and policy leads to accelerate the integration of Generative AI (GenAI) methods in chemistry education. Building on last year’s event\, the focus moves decisively beyond abstract debate toward classroom-ready practice\, shared resources\, and cross-institutional learning.Aligned with the AIchemy Hub mission\, the workshop will advance the UK-wide conversation through three interconnected themes that reflect real teaching\, learning\, and institutional needs: \n\n\n\nPractical implementation of GenAI in chemistry teaching and laboratoriesExplore how AI can be meaningfully embedded into undergraduate teaching and laboratory practice. Sessions will focus on the co-design of AI-integrated experiments\, inclusive laboratory tools\, and transferable teaching resources. Participants will contribute to shaping a shared repository of AI-enabled laboratory and assessment activities. \n\n\n\nAI in assessment\, feedback\, and curriculum designExamine how AI can act as a co-pilot for educators\, supporting assessment design\, feedback generation\, curriculum review\, and bias reduction. This theme supports the development of shared tools and best practice to help bridge the AI–chemistry skills gap for both staff and students. \n\n\n\nInstitutional strategy\, policy\, and ethics grounded in real practiceEngage with institution-level strategies and ethical frameworks for the responsible use of GenAI in chemistry education. By comparing approaches across UK universities\, this strand will highlight shared principles\, practical challenges\, and transferable exemplars to support ethical implementation in teaching and assessment. \n\n\n\n\n\n\n\nCall for Lightning Talk Abstracts \n\n\n\nWe invite submissions for short lightning talks that showcase practical and innovative uses of AI in chemistry education. This is an opportunity to share your practice\, ideas\, and lessons learned with colleagues from across the UK\, and to contribute to a growing national conversation on how AI is shaping chemistry teaching and learning. We particularly welcome abstracts featuring case studies from teaching practice\, AI-enabled laboratory experiments\, assessment and feedback approaches\, curriculum design initiatives\, and student–staff co-created projects.During registration\, you will be able to indicate your interest in giving a lightning talk and submit a short abstract\, after which the organising team will be in touch with further details. The deadline for lightning talk submissions is 1 May 2026. \n\n\n\n\n\n\n\nWho Should Attend: \n\n\n\nThis workshop is aimed at academics working in chemistry with an interest in teaching and education\, as well as teachers and staff from colleges and secondary schools who want to better understand future university pathways for their students. It will also be valuable for anyone seeking insight into how artificial intelligence is shaping the next generation of chemistry education across the UK. \n\n\n\nWhat you’ll gain: \n\n\n\n\nGain insight into the current UK higher-education curriculum landscape for AI in chemistry\n\n\n\nUnderstand how GenAI is being implemented across undergraduate and postgraduate taught courses\, in both lectures and laboratories\n\n\n\nExplore challenges\, risks\, and opportunities in real-world adoption\n\n\n\nDevelop ideas for new lab-based experiments and training using AI methods such as machine learning (ML)\, convolutional neural networks (CNNs)\, and Bayesian optimisation (BO)\n\n\n\n\n\n\nSpeakers– To be Announced\n\n\n\n\n\n\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubUniversity of WarwickUniversity of GlasgowDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr. Chris Mellor (Imperial)Aysel Sarzosa Llerena (Imperial)Tom RitchieDr Dani PearsonDr Ciorsdaidh Watts
URL:https://aichemy.ac.uk/event/gen-ai-in-chemistry-education/
CATEGORIES:Symposium
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DTSTART;TZID=UTC:20260901T090000
DTEND;TZID=UTC:20260903T170000
DTSTAMP:20260412T190404
CREATED:20260313T125151Z
LAST-MODIFIED:20260330T111839Z
UID:8245-1788253200-1788454800@aichemy.ac.uk
SUMMARY:Chemical Artificial Intelligence in Homogeneous Catalysis (ChemAICat) Workshop
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE1 -3 SEPTEMBER 2026 TIME09:00 – 17:00 COST£75 – ACADEMIA £150 – INDUSTRY REGISTRATION DEADLINE14 AUGUST 2026 \n\n\n\nApply Now\n\n\n\nagenda\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nUNIVERSITY OF LIVERPOOLMaterials Innovation Factory\, 51 Oxford St\, Liverpool\, L7 3NY \n\n\n\n\n\n\n\n\nAbout the Workshop\n\n\n\nThe Chemical Artificial Intelligence in Homogeneous Catalysis (ChemAICat) workshop held at University of Liverpool offers a practical guide to different AI techniques that can be applied to accelerate or complement research in homogeneous catalysis. It is especially recommended for experimental and computational chemists with basic or no Python programming experience. The classes aim to provide these researchers with ready-to-use workflows that they can introduce into their routine research tasks. Some of the protocols covered include: \n\n\n\n\nBasics of Python and cheminformatics\n\n\n\nAutomated descriptor generation from ChemDraw and CSV files\n\n\n\nData-driven and efficient chemical exploration for catalyst sampling\n\n\n\nAI-driven optimization of reaction conditions\n\n\n\nAI-driven catalyst discovery\n\n\n\n\n\n\n\n\nWho Should Attend: \n\n\n\nThis workshop is aimed at experimental and computational chemists working in homogeneous catalysis with little or no experience in Python. The workshop is suitable for the following career stages: PhD students\, postdoctoral researchers and Early Career Academics. \n\n\n\n\n\n\n\nPre-Requisites: \n\n\n\nTo help you get the most from the workshop\, please ensure the following are completed in advance: \n\n\n\n\nAttendees must bring their own laptops to run the programs used during the workshop. Windows\, macOS and Linux operating systems are supported.\n\n\n\nComplete a preliminary setup to install the required Python environments. Instructions will be provided a few weeks before the workshop and should take 30-60 minutes to complete.\n\n\n\n(Optional) Share custom problems in advance that could be included in the problem-solving sessions. This will allow the workshop to focus on topics that are most relevant to the audience\n\n\n\n\n\n\nHow to apply\n\n\n\nPlaces are limited and to ensure a balanced mix of expertise and perspectives we are asking applicants to apply. As demand is expected to be high\, we ask all interested participants to complete the application form by 26th June 2026 and decisions will be given to applicants by 10th July 2026.Please note: all bookings are non-refundable. \n\n\n\n\n\n\n\n\n\n\n\n\n\nAccommodation and Travel\n\n\n\nPlease note that the registration fee does not include accommodation\, travel or subsistence. Participants are responsible for arranging their own accommodation and transport during the ChemAICat Workshop.We are happy to recommend the Novotel Liverpool Paddington Village\, a modern hotel conveniently located within walking distance of the University of Liverpool campus. This hotel offers comfortable rooms\, breakfast options and easy access to local amenities.A social networking event will be hosted on one evening (day to be confirmed) during the school and is included in the registration.For those seeking alternative options\, Liverpool offers a wide range of hotels\, serviced apartments\, and budget accommodations within easy reach of the University.Liverpool is well-connected by rail\, with Liverpool Lime Street Station approximately a 10-minute walk from the University campus. For those travelling by car\, parking is available at the Paddington Village Car Park\, located close to the University and the recommended hotel. \n\n\n\nAirports\n\n\n\nLiverpool John Lennon Airport (LPL) – Around 30 minutes from the University by taxi or public transport. The airport offers flights to many UK and European destinations.Manchester Airport (MAN) – Around 1 hour by train or car\, with direct rail connections to Liverpool Lime Street. This airport provides a wide range of international flight options. \n\n\n\n\n\n\n\n\n\n\n\n\n\nCourse Supervisors\n\n\n\nDr. Jamie Cadge (University of Bath) \n\n\n\nDr. Ruben Laplaza (IIQ\, University of Seville-CSIC) \n\n\n\nDr. Thijs Stuyver (PSL University) \n\n\n\nDr. Juan V. Alegre-Requena (ISQCH\, University of Zaragoza-CSIC) \n\n\n\n\n\n\n\n\n\n\n\n\n\nContact Details\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk \n\n\n\n\n\nThe Organising Committee\n\n\n\nAIchemy HubUniversity of LiverpoolCourse SupervisorsDr Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Jean-Francois AymeDr. Jamie Cadge (University of Bath)Dr. Ruben Laplaza (IIQ\, University of Seville-CSIC)Dr. Thijs Stuyver (PSL University)Dr. Juan V. Alegre-Requena (ISQCH\, University of Zaragoza-CSIC)
URL:https://aichemy.ac.uk/event/chemical-artificial-intelligence-in-homogeneous-catalysis-chemaicat/
CATEGORIES:Symposium
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DTSTART;TZID=UTC:20261123T000000
DTEND;TZID=UTC:20261127T235959
DTSTAMP:20260412T190405
CREATED:20260220T124659Z
LAST-MODIFIED:20260223T110627Z
UID:7897-1795392000-1795823999@aichemy.ac.uk
SUMMARY:Winter School: Robotics and AI for Materials Chemistry 2026
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE23 – 27 NOVEMBER 26 ACADEMIC PARTICIPANTS£150 INDUSTRY PARTICIPANTS£300 \n\n\n\nAPPLY HERE\n\n\n\n agenda COMING SOON\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nNovotel Hotel\, University of Liverpool Campus3 Paddington Village\, Liverpool\, L69 7ZD \n\n\n\n\n\n\n\n\nThe Robotics and AI for Materials Chemistry Winter School is a five-day intensive training programme focused on digital and automated chemistry\, robotic systems\, and AI-driven scientific discovery. Hosted at the University of Liverpool\, the school is designed for PhD students and early-career researchers\, or those new to digital chemistry and AI\, and who want to build their capabilities in this rapidly evolving field. A strong working knowledge of Python is required to fully benefit from the practical sessions and technical content. \n\n\n\nThis Robotics and AI for Materials Chemistry Winter School will: \n\n\n\n\nProvide essential skills in digital chemistry\n\n\n\nStrengthen understanding of AI and machine learning\, building on participants’ existing knowledge\n\n\n\nOffer hands-on experience with key tools and techniques for automated\, intelligent lab environments\n\n\n\n\nParticipants will explore a range of cutting-edge topics\, including: \n\n\n\n\nDigital twins for robotic chemists\n\n\n\nBayesian optimisation for chemical discovery\n\n\n\nAI-driven robotic chemists\n\n\n\nRobotic manipulation for lab automation\n\n\n\nSimulation of robotic chemists\n\n\n\nComputer vision-led chemistry\n\n\n\nMulti-modal machine learning for science\n\n\n\nAgentic AI-based discovery\n\n\n\nHuman-in-the-loop robotic discovery\n\n\n\n\nAfter a hugely successful 2025 Winter School\, we’re delighted to bring it back for 2026. Take a look at last year’s programme and highlights to see what to expect. \n\n\n\n\n\nProvisional Programme – Coming Soon\n\n\n\n\n\n\n\nSpeakers – To be announced\n\n\n\n\n\n\n\n \n\n\n\nAccommodation and Travel\n\n\n\nPlease note that the registration fee does not include accommodation\, travel or subsistence. Participants are responsible for arranging their own accommodation and transport during the Winter School. \n\n\n\nWe are happy to recommend the Novotel Liverpool Paddington Village\, a modern hotel conveniently located within walking distance of the University of Liverpool campus. This hotel offers comfortable rooms\, breakfast options and easy access to local amenities. \n\n\n\nA social networking event will be hosted on one evening during the school and is included in the registration. \n\n\n\nFor those seeking alternative options\, Liverpool offers a wide range of hotels\, serviced apartments\, and budget accommodations within easy reach of the University. \n\n\n\nLiverpool is well-connected by rail\, with Liverpool Lime Street Station approximately a 10-minute walk from the University campus. For those travelling by car\, parking is available at the Paddington Village Car Park\, located close to the University and the recommended hotel. \n\n\n\nAirports:\n\n\n\n\nLiverpool John Lennon Airport (LPL) – Around 30 minutes from the University by taxi or public transport. The airport offers flights to many UK and European destinations.\n\n\n\nManchester Airport (MAN) – Around 1 hour by train or car\, with direct rail connections to Liverpool Lime Street. This airport provides a wide range of international flight options.\n\n\n\n\n\n\n\n\nHow to Apply:\n\n\n\nPlaces are limited and to ensure a balanced mix of expertise and perspectives we are asking applicants to apply. As demand is expected to be high\, we ask all interested participants to complete the application form by 24th August 2026 and decisions will be given to applicants by 31st October 2026. \n\n\n\nPlease note: all bookings are non-refundable. \n\n\n\n\n\n\n\nContact details:\n\n\n\nFor questions related to this event please contact the AIchemy project management team at info@aichemy.ac.uk. \n\n\n\n\n\n\n\n\nThe Organising Committee:\n\n\n\nAlchemy HubUniversity of LiverpoolDr. Ben Alston (University of Liverpool) Caroline Woods (University of Liverpool)Dr Gabriella PizzutoDr Xenofon EvangelopoulosProf. Alessandro TroisiMinh CaoDr Mengjia ZhuDr Xin Yang
URL:https://aichemy.ac.uk/event/winter-school-robotics-and-ai-for-materials-chemistry-2026/
CATEGORIES:Training School
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