229 computational-physics-"https:"-"https:"-"https:"-"https:"-"Dr" Postdoctoral positions in United Kingdom
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The Qing Laboratory at Oxford is recruiting postdoctoral researchers (multiple positions available) to join a Bill & Melinda Gates Foundation–funded programme focused on developing innovative
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archaea, many of which also use histones as major chromatin building blocks, and non-model bacteria. In the lab we combine a variety of computational and experimental techniques, including phylogenomics
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to improve the impact of AI on global societal outcomes through impactful research that is rigorously grounded in the social and computational sciences, decision-maker education campaigns, and training
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an ongoing programme focused on metabolic profiling and target validation to support TB drug discovery. The role will involve the application of liquid chromatography–mass spectrometry (LC-MS
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2025). Our microchip-based escape-time technology platform now enables measurements of the physical properties of macromolecules such as their electrical charge, size and 3D conformation with
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tuberculosis . The post is full-time and available immediately. The post holder will be responsible for carrying out research within a defined area of an ongoing programme focused on metabolic profiling and
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. Applicants must hold a PhD in Chemistry or Physics (or be close to completion) or a relevant subject area to taking up the appointment. You will be expected to work well as a part of the team, and contribute
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computational docking and/or AI-assisted predictive tools. All molecules will be screened using in vitro and cell-based platforms established in our team, and the best will be continued to more advanced models
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Martin AI Governance Initiative (AIGI Oxford) seeks to improve the impact of AI on global societal outcomes through impactful research that is rigorously grounded in the social and computational sciences
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We are looking for a Postdoctoral Research Associate reporting to the Principal Investigator Prof Yee-Whye Teh, they will be a member of the Oxford Computational Statistics and Machine Learning