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students who are eager to develop and apply artificial intelligence techniques and mechanistic mathematical models to explore fundamental questions in biology. The PhD program is organized in partnership
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, and climate-sceptic arguments — particularly in relation to decarbonising agriculture — are reproduced and normalised within Irish news media and public discourse. The PhD candidate will play
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in their decisions and businesses in their strategies. You will join the Intelligent and Clean Energy Systems (ICES) research unit at the Luxembourg Institute of Science and Technology (LIST) and will
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Foundation (www.synthera.eu/ ). We are seeking an excellent and enthusiastic Ph.D. student with a strong interest in computational microbiome research. The specific focus of the Ph.D. project will be tailored
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in their decisions and businesses in their strategies. You will join the Intelligent and Clean Energy Systems (ICES) research unit at the Luxembourg Institute of Science and Technology (LIST) and will
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knowledge and/or experience in several of the following topics: Optimisation algorithms Machine learning algorithms Swarm intelligence Algorithmics Parallel/Distributed computing Space systems engineering
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I-2503 – PHD IN EXPLAINABLE AI FOR DATA-DRIVEN PHYSIOLOGICAL AND BEHAVIORAL MODELLING OF CAR DRIVERS
for Next Generation of Pneumatic Tires, Structure-Process-Properties Relationships. As part of our Data Science strategic research program, we are looking for a PhD candidate in artificial intelligence and
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experimental and computational methods to understand membrane protein transport and signalling processes. The focus is to develop novel structural biology techniques with the aim to understand membrane protein
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., scientific papers, software, reports, project deliverables) · Supporting other researchers working in the group / unit · Contributing to the group / unit objectives The Intelligent and Clean Energy
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. The BayesCompare project is a FNR funded project on Bayesian comparisons between artificial and natural representations to improve our understanding how natural and artificial intelligences process information