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the groups of Dr Joe Forth, Dr Anthony Bradley, and Project Lead Professor Steve Rannard, applying your expertise in machine learning, cheminformatics, and soft materials to accelerate LAT design and
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asynchronous AI-led chemical optimisation across chemistry laboratories¿. This role sits at the intersection of robotics, machine learning, and chemistry, aiming to develop robotic systems that work
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of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability to manage
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the area of probability of statistical machine learning. They will possess sufficient specialist knowledge in network analysis and uncertainty quantification in machine learning and have the ability
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predictive control of carbon mineralisation through high-throughput mineralogy and machine learning.” This is an exciting opportunity to contribute to innovative research at the interface of mineralogy
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Engineering, Mathematics, Statistics, Computer Science or conjugate subject and have a strong record of publication in the relevant literature. Good knowledge of machine learning algorithms is essential, as
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Applications are invited for a Postdoctoral Research Associate in Machine Learning for Chemistry to work in the research group of Professor Volker Deringer at the Department of Chemistry. About the
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Are you passionate about using data science and machine learning to address mental health inequalities in rural and coastal communities? The University of Lincoln is seeking an ambitious
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of pursuing external funding. Experience of computational chemistry techniques. Experience in cheminformatics, machine learning and/or algorithm development for chemical synthesis. Experience with UNIX and HPC
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collaboration with Dr Whelan and the PhD students, machine learning tools for the handling of the Mauve and MUSE datasets. They will also be expected to lead the research into innovative ways in which the machine