88 computational-complexity-"Prof"-"Prof" Postdoctoral positions at University of Oxford
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of code to conduct complex comparative genomics, implement HMM searching strategies and conduct phylogenetic analysis on a grand scale while making use of sophisticated phylogenetic methods (for example
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of collaborative projects, working closely with clinicians, imaging experts, and computational scientists across the Oxford–Novartis Collaboration for AI in Medicine. You must hold a PhD/DPhil in Statistics
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quantification. Find out more about the research and group here. Your Role As a postdoc on this project, you will be part of a dynamic team working at the intersection of computational biology, molecular
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, including the generation and analysis of complex datasets is desirable. Excellent communication skills, including the ability to write for publication and represent the research group at meetings
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research programme on “Enabling consumers to make healthy financial choices”, focusing on how technological and organisational solutions can improve financial literacy and decision-making. This post, under
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’ programme grant. Find out more about the research and group at: About you Applicants must hold a PhD in Physical Chemistry or a related area, (or be close to completion) prior to taking up the appointment
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, complex protein chemistry, and challenging biophysics including development of new assays would all be a plus. Enthusiasm for working in a laboratory environment and in a small team is also expected, as
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to a large-scale, interdisciplinary research programme. We are looking for someone with proven expertise in a fast-paced environment, who is committed to delivering high-quality research support and
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role in participating in the exchange programme with Johns Hopkins University. You will also be responsible for contributing new research project ideas, managing your own administrative activities and
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Raman’s cardiovascular research team. This role is embedded within a cutting-edge programme focused on integrating high-dimensional datasets, including advanced cardiac MRI (oxygen-sensitive, metabolic, and