11 postdoc-in-thermal-network-of-the-physical-building Fellowship positions at Imperial College London
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linked position at NCBS Bangalore that starts after the completion of the first year at Imperial). Details of the NCBS Bangalore position can be found at https://www.ncbs.res.in/academic/postdoc-ai-in
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part of this strategy, we have identified four research themes that span grand societal and technical challenges that are also areas in which we believe our department will continue to make substantial
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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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Mission. You will deepen UKERC’s research capabilities, complementing existing strengths. You will build on a successful programme of activity focused on risk and investment in energy markets, working
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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themes are not covered, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
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navigating your career and managing research as well as a transparent promotion process. Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes). Be part of a
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of the project, with the support of the supervisors and the wider team. The post-holder will be responsible for the background research necessary to construct a model that represents the onset and progression