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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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) analysis Mathematical modelling Microbiology Molecular biology We approach science with the view of physics, aiming to identify principles behind complex systems. We collaborate closely with engineers
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in physics, mathematics or any related field; correspondingly, Postdocs hold a PhD or equivalent degree in the abovementioned fields. What we offer State of the art on-site high performance/GPU compute
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analysis with practically motivated case studies, offering a strong foundation for researchers interested in advancing the mathematical understanding of geometric deep learning. Your Qualifications PhD
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To qualify for the fellowship, the candidate should hold a PhD degree, or a foreign degree that is deemed equivalent to physics, mathematics, or molecular biology. But more importantly, the candidate should
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of results in scientific journals Requirements PhD in Physics, Engineering, Economics, Environmental Sciences, Mathematics, System Sciences or a related field training in formal, quantitative methods
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schizophrenia. Preference will be given to applicants who have received their Ph.D. degrees in computational neuroscience, physics, mathematics, computer science, or related fields within the last 3 years and
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skills in data analysis, machine learning, as well as in mathematical and computational modelling? You will have the opportunity to investigate innovative solutions using machine learning algorithms and
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to illness, parental leave, clinical service, trade union duties or similar circumstances. The PhD degree should be in a computational or life science field, such as bioinformatics, ecology, mathematics
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surface properties on their energy balance and gas exchange. Experiments will be accompanied by mathematical modelling of the physical processes involved. How will you contribute? In accordance with any