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—to macroscopic, population-level observables in rapidly evolving pathogens such as SARS-CoV-2 and influenza. Concretely, you will: formulate and analyze stochastic models of evolving populations using methods from
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on numerics and analytics, an interest in modeling, and a genuine interest in engaging in the biological system and working closely with our collaborators Job requirements Masters in Physics
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team as a PhD candidate to work on beyond the state-of-the-art model distillation and robustness methods, enabling efficient, reliable inference for challenging real-world problems in the semiconductor
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PhD position: Global soil mapping with process-informed machine learning Faculty: Faculty of Geosciences Department: Department of Physical Geography Hours per week: 36 to 40 Application deadline
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Modelling for Dementia Support Technologies Our goal: This PhD project is part of the European project DEM-CAPS (www.demcaps.org ) aimed at developing and validating a health-economic modelling framework
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of the applied currents, leading to large parameter spaces for applications. To optimize tACS towards a technique of network stimulation in the human brain, we use computational modeling at the population level