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engineering science, with knowledge and/or some experience of energy technology and policy; and/or quantitative analysis including econometrics, statistics and machine learning and related disciplines handling
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medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and astrostatistics. These posts
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. The researcher would be expected to have knowledge of protein structure, protein ligand binding, machine learning and expertise in workflow development. Information generated by the project will be widely
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to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
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Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
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People from Deepfakes Project. We are looking for a software/machine learning engineer (or similar) to work in an interdisciplinary team reporting to Dr Sophie Nightingale (Principal Investigator
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. You would be the day-to-day supervisor for two PhD students on this levitated microdiamond project, as well as helping to supervise undergraduate project students. Applications from underrepresented
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Introduction As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill
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of the research of Associate ProfessorDr Thomas Wälchli, MD-PhD, FMH neurosurgery is to understand how the brain vasculature is regulated during brain development, in the adult healthy brain, and in various
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Oxford Institute. This role would be suitable for individuals who have or are working towards completing a PhD/DPhil by the closing date for these posts. About us Based in Littlegate House, the Uehiro