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Title: Disentangling and modelling behaviourally-relevant visual and semantic dimensions of visual cognition in the human brain (Kamila Maria Jozwik lab, the University of Cambridge)Application
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programme aims to advance fundamental understanding of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key
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international research grants and is currently scaling up its research capacity – in 2026, we are expanding with four postdocs who are expected to work closely with the ph.d. students hired in this call. As a PhD
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from open water and polynyas drive snowfall and melt events; and running regional climate model simulations to project future Greenland surface mass balance under different sea ice scenarios. You will
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experience in in mathematical modelling and forward genetic simulations using SLIM - information provided in the CV and/or in the motivation letter; Experience in experimental evolution and/or genomic and/or
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technologies, drug discovery and advanced therapeutics. We have excellent facilities to support our parallel use of pre-clinical cell and in vivo models, alongside human cellular models, which provide
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. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process & microstructure with
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collaborative, vibrant, and growing research community including 12 Associate Professors and Professors, 23 PhD candidates, researchers, and postdocs, and 4 engineers. As a PhD Candidate with us, you will work
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environmental change. The BEE section is a collaborative, vibrant, and growing research community including 12 Associate Professors and Professors, 23 PhD candidates, researchers, and postdocs, and 4 engineers
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer