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Field
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topic from the areas represented within the group. The group’s interdisciplinary focus includes not only classical topics in numerical analysis, such as the analysis of nonlinear PDEs, but also modeling
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Associate with mathematical modelling and numerical/data analysis background to join our food system resilience project, led by University of Reading, joining a large interdisciplinary team with an excellent
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optimizing simulation tools such as CalPhad to support experimental findings. Conducting in-depth metallographic analysis and establishing correlations between mechanical properties and microstructural
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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used in our work centre around optical imaging and spectroscopy and nanofabrication. The work also relies on theory and simulation, specifically focusing on numerical mean-field electrostatics
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reliable, safe, and secure software systems, carrying out both upstream activities such as requirements quality assurance and architecture analysis, as well as downstream verification & validation activities
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Qualifications / Experience: • A PhD in Physics, Geoscience or a related field • Proven expertise in numerical modelling using super computing clusters • Excellent knowledge of atmospheric physics • Proficiency in
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+ imaging, data analysis and neuronal circuits. Requirement PhD in neuroscience, computer science or a related field High motivation for explorative research Experience in neurophysiology (electrophysiology
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can be found at the URL https://math.univ-cotedazur.fr/~ingremeau/PostdocNuHeMiBa.pdf We are looking for a candidate with a PhD in applied mathematics, with a strong focus on numerical analysis
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. The growing region surrounding Fayetteville is home to numerous Fortune 500 companies and one of the nation’s strongest economies. Northwest Arkansas is also quickly gaining a national reputation for its focus