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Postdoctoral Researcher in Machine Learning of Isomerization in Porous Molecular Framework Materials
broad range of applications. Computational chemistry and Machine Learning increasingly underlies MFM research to search or screen candidate MFMs prior to synthesis. A major drawback when applying
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About the role The Kelly lab is excited to announce a new post-doctoral position in computational biology. This position is funded as part of an international consortium of scientists who
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dedicated to development, translation and clinical application within medical imaging and computational modelling technologies. Our objective is to facilitate research and teaching guided by clinical
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their FTE). Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided by Heriot-Watt University Role Description We are seeking
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excellent computational skills. The post is attached to Prof. Eric French's Montague Burton Professorship. The research aims at exploring and understanding the drivers of medical spending, and how medical
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the starting date is negotiable. The current funding is guaranteed from the Montague Burton Fund. We are looking for a candidate who is a health economist with excellent computational skills. The post is
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the field of atomic. molecular and optical physics within the Durham Quantum Light and Matter group. The positions are associated with a new five-year Programme Grant on "Quantum Many-Body Physics with
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numerical modelling. Ability to participate in research meetings to troubleshoot research problems and discuss the direction of research. Skills Fluency in at least one scientific computer language (e.g., C
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associated microbes are particularly encouraged. Laboratory management experience, molecular skills, and experience with simple bioinformatics and computational statistics are highly desirable. Please ensure
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve