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DTSTART;TZID=UTC:20260311T000000
DTEND;TZID=UTC:20260415T235959
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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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DTSTART;TZID=UTC:20260413T000000
DTEND;TZID=UTC:20260417T235959
DTSTAMP:20260412T101937
CREATED:20251027T135314Z
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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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DTSTART;TZID=UTC:20260422T140000
DTEND;TZID=UTC:20260422T150000
DTSTAMP:20260412T101937
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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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