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This role sits within the Faculty of Technology, Arts and Culture / School of Creative Industries and Culture. The post is part of the funded UKRI project Entrepreneurship, Art and Science for
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application! Your work assignments Spatio-temporal processes are everywhere in science and engineering, with applications ranging from weather prediction to cardiovascular medicine. Developing machine learning
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PhD Position in Physiological Tree Ecology 100 % / starting July 2026 or later The Physiological Plant Ecology group at the Department of Environmental Sciences at the University of Basel in
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into useful chemical products is at the heart of the Net Zero transition. In liquid-phase heterogeneous systems, controlling which product forms and understanding why it forms remain one of the field's most
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modeling with experimental validation and has two major objectives: Development of a physics-informed neural network (PINN) framework You will design and implement a simulation framework to model
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events with the GOTO telescope network. Projects focussing on thermonuclear bursts will involve analysis of new and archival data from satellite-based X-ray telescopes, and running numerical models
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research within the EUArthurs network, funded by the European Commission’s Marie Skłodowska-Curie Actions ("European Arthurs, Medieval to Modern", see CORDIS project link). The candidate will undergo
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HBIGS Heidelberg Biosciences International Graduate School | Heidelberg, Baden W rttemberg | Germany | 27 days ago
25 Mar 2026 Job Information Organisation/Company HBIGS Heidelberg Biosciences International Graduate School Research Field Biological sciences » Biology Researcher Profile First Stage Researcher (R1
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About Us The successful candidate will join our new MSCA Doctoral Network: VISIONBRAIN - Cutting-edge Human In Vitro And In Silico Biomedical Tools On Brain Disorders. This EU-funded project will
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photonic systems, in particular, make it possible to harness the richness of optical dynamics to perform complex operations inspired by biological neural networks. However, current approaches face