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the interface of computational biology, molecular science and translational medicine, generating large multi-omic datasets that require robust, reproducible analysis to identify rare signals with high accuracy
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to an internationally significant research programme and help shape new directions in the social science of biosecurity. This post is fixed term for 3 years with the possibility for an extension and offered on a full
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Ecological Sciences at the University of Liverpool (UoL), UK. The position is funded by a Natural Environment Research Council (NERC) Pushing the Frontiers award 'CALDERA: Collaborative Approach to integrate
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. About You You will have, or be close to completion of a PhD/DPhil in Statistics, Machine Learning, Data Science, or a related quantitative discipline. You will demonstrate strong specialist knowledge in
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of future research proposals. Skills, Experience & Qualifications Needed PhD in an appropriate subject area (awarded or submitted). Proficiency in Python for scientific computing, including basic scientific
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are looking for a researcher with a PhD (or near completion) in engineering, data science, computational social science or a related discipline, with experience in data analytics, NLP or machine learning. You
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, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding experience with producing high-quality
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should possess: • A PhD/DPhil (or near completion) in Engineering, Materials Science, Physics, or a related field • Strong expertise in composite materials, their deformation and failure, and finite
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. statistics, mathematics, computer science, statistical or population genetics, or a related discipline), and a strong motivation to work on problems in genetics and you will also have relevant coding
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. The broader goal of the overall programme, funded through the Wellcome Trust bioimaging technology development initiative, is to deliver multimodal datasets in an interoperable manner through open access