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differential equations relevant to computational fluid dynamics. These efforts might include Bayesian physics-informed neural networks and neural operators. Bayesian neural networks for approximating piecewise
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from candidates with an M.Sc. degree (or equivalent, including candidates who are about to complete their degrees) in materials science, chemistry, physics, or related fields. In addition to the above
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of density functional theory (DFT) is beneficial but not required. Your workplace You will work in the Theoretical Physics Division: https://liu.se/organisation/liu/ifm/teofy . The division conducts research
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inherently spatio-temporal, i.e. physical processes around us evolve over both time and space, making spatio-temporal processes and data omnipresent in science and technology, with applications ranging from
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application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is inherently spatio-temporal, i.e. physical processes