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of development stochastic models that explain the population behaviour of immune cells subject to controlled stimulation, you will collaborate in research that seeks to explain the weak inheritance features
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Reference Number BAP-2026-5 Is the Job related to staff position within a Research Infrastructure? No Offer Description This PhD project centers on the development of a computational platform model for a
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dysfunction. Building on more than two decades of development stochastic models that explain the population behaviour of immune cells subject to controlled stimulation, you will collaborate in research
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assistants and formalization of mathematics (e.g., Lean, Coq, Isabelle) Automated reasoning for mathematics (e.g., SAT/SMT solvers, first-order theorem provers) Machine learning for mathematics (e.g., model
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student-centered university. The successful candidate will have a PhD in Mathematics, Physics or related field or extensive applicable experience and must be able to teach lab-based courses. The candidate
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predictive mathematical framework for these interactions—particularly in eccentric orbits—remains incomplete. This PhD project will develop and analyse theoretical models describing the secular evolution
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spaces for applications. To optimize tACS towards a technique of network stimulation in the human brain, we use computational modeling at the population level (neural mass models) as well as at the neuron
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, conversely, to use clinical observations to develop new research ideas. The aim is to deliver medically relevant benefits to patients and the general population. The BIH PhD Program contributes to the overall
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of research outcomes. Supervise or mentor junior researchers and students when appropriate. Qualifications and experience PhD in engineering, computer science, bioinformatics, applied mathematics, neuroscience
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mitochondrial behaviour. This is one of two PhD positions in “MitoPhyto” hosted at the Department of Mathematics, where this focusses on mathematics and modelling and the other is more focused on experimental