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within a cross-functional team, including software developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and
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cellular dynamics. Analyze large-scale transcriptomic and spatial dynamics datasets. Work in close collaboration with the team's biologists to test predictions from statistical models. Within the Polarity
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’ (PHOENIX), led by Associate Professor Thomas Aubry (University of Oxford). Using a combination of laboratory experiments, field work and numerical modelling, PHOENIX aims to improve our understanding
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modeling. Positions may begin as soon as September 2025 . A Ph.D. in Mechanical and Aerospace Engineering, Civil and Environmental Engineering, Atmospheric and Oceanic Sciences, Geosciences, Computational
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of the near critical Ising model, or the massive Thirring model. Qualifications We are looking for applicants with a PhD in mathematics or theoretical physics, with experience in mathematically rigorous
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contribute to smart grids that make energy networks more efficient, mathematical models that assist medical doctors, schedules that make hospitals more efficient and numerical schemes to study multiscale fluid
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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on the development of mathematical and computational models of biological systems. This position is supported by an NIH Virtual Consortium for Translational/Transdisciplinary Environmental Research (ViCTER) grant, “In
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sequences, with applications ranging from biogeographical mapping to paleogenetic reconstructions. The candidate will work jointly with Dr. Eran Elhaik to design machine-learning models that unlock
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at Michigan Tech. The work will focus on building advanced reservoir simulation models coupled with geomechanics, performing risk assessments using NRAP tools, and contributing to leakage risk quantification