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DTSTART;TZID=UTC:20250521T150000
DTEND;TZID=UTC:20250521T160000
DTSTAMP:20260413T053924
CREATED:20250315T073308Z
LAST-MODIFIED:20250731T134822Z
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SUMMARY:AIchemy’s Monthly Webinar Series – May 2025
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE21 May\, 2025 TIME15:00 – 16:00 COSTFree \n\n\n\nREGISTRATION CLOSED\n\n\n\n\n\n\nRECORDINGSClick the YouTube links below to watch each session. \n\n\n\n\nApproximate Bayesian Inference for Spectroscopy with Varying Pure Component Signals Development of ML methods for reaction optimization and prediction \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\nJames Odgers – Approximate Bayesian Inference for Spectroscopy with Varying Pure Component Signals \n\n\n\nSpectroscopy is a widely applied technique for monitoring chemical processes and the physics underpinning the technique is well understood. However\, when making quantitative predictions the physical basis for spectroscopy is typically discarded due to complex effects of the environment on the observed spectral signals. In this work we present a non-parametric Bayesian approach to model the effects of changing conditions\, allowing an interpretable\,  physics informed model to be applied in more challenging situations.  \n\n\n\nProf. Abigail Doyle – Development of ML methods for reaction optimization and prediction \n\n\n\nMachine learning (ML)\, the development and study of computer algorithms that learn from data\, is increasingly important across a wide array of applications\, from virtual personal assistants to social media and product recommendation systems. ML methods have also driven key developments in the natural sciences: virtual screening of drug-like molecules for medical applications\, rapid prediction of physical data\, and computer-aided synthesis planning have all been facilitated by ML. The development of ML tools for synthetic methodology development and catalysis could enable chemists to make data-efficient choices and learn from that data in the course of reaction prediction\, reaction condition optimization\, and mechanistic interrogation. This lecture will describe my group’s efforts to develop and apply open-source data science tools to numerous aspects of synthetic methodology development\, including substrate scope design\, ligand discovery\, reaction optimization and mechanistic elucidation. \n\n\n\nFollowing the presentations\, there will be time for questions from the audience.We look forward to having you attend the event! \n\n\n\n\n\nSpeakers\n\n\n\n\n\nJames OdgersPhD Student\n\n\n\n\n\nAbigail DoyleProfessor of Chemistry\n\n\n\n\n\nKeith Butler – Webinar Chair Associate Professor in Computational Materials Chemistry
URL:https://aichemy.ac.uk/event/aichemys-monthly-webinar-series-may-2025/
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=UTC:20250521T183000
DTEND;TZID=UTC:20250521T210000
DTSTAMP:20260413T053924
CREATED:20250415T103304Z
LAST-MODIFIED:20250605T152137Z
UID:3316-1747852200-1747861200@aichemy.ac.uk
SUMMARY:Pint of Science @ Liverpool
DESCRIPTION:KEY DETAILS\n\n\n\n\nDATE21 May\, 2025 TIME1830 – 21:00 COST£5 \n\n\n\nSOLD OUT\n\n\n\nREAD THE HIGHLIGHTS BLOG\n\n\n\n\n\n\nEVENT LOCATION\n\n\n\n\nFrederiks32 Hope Street\,\nLiverpool L1 9BX \n\n\n\n\n\n\n\n\n\n\n\n\nJoin us for a night where artificial intelligence meets actual intelligence – yours\, after a pint or two. You’ve heard of AI and GPT – now meet the scientists using it to change the world. Discover how AI is revolutionising chemistry\, engineering\, and even the nuclear industry. Come for the cutting-edge science\, stay for the cold pints and curious conversations.
URL:https://aichemy.ac.uk/event/pint-of-science-liverpool/
CATEGORIES:Webinar
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