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, depending on the selected field of view. In parallel with the handling of the experimental system, the PhD student will develop laser-induced fluorescence simulation codes for the species under investigation
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responses. To do this the candidate will develop and refine protocols that integrate simultaneous measurements of behaviour, metabolism and stress hormones. Complementing the parallel PhD project (Position
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optimization in distributed systems. The work also involves modern compiler infrastructures, with emphasis on MLIR, and contributions to LLVM and the OpenMP standard. Applicants must hold a PhD in Computer
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protocols that integrate simultaneous measurements of behaviour, metabolism and stress hormones. Complementing the parallel PhD project (Position One), this position focuses on cod and includes
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computing software libraries (e.g., Trilinos, MFEM, PETSc, MOOSE). Experience with shared and distributed memory parallel programming models such as OpenMP and MPI. Experience with one more GPU or performance
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. Required PhD in Computer Science / AI / Machine Learning Strong publication record in AI, ML systems, or related areas Strong programming skills in Python, C/C++ and experience with PyTorch, TensorFlow, JAX
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commuting to the assigned work location when necessary. Qualifications We Require: PhD in engineering, physics, applied mathematics, computer science or other relevant field Ability to obtain and maintain a
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LevelPhD or equivalent Skills/Qualifications Who you are You have a PhD, preferable in Computer Science, Engineering, Mathematics, or equivalent. You have a strong background with parallel and distributed
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computational approaches, including in vivo Massively Parallel Reporter Assays (MPRAs), to define the sequence basis and functional consequences of enhancer activity and to expand MPRA-based approaches to other
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: Recent PhD and/or MD in a relevant field, or equivalent research experience, with a background in molecular biology, transcriptional regulation, functional genomics, computational biology, genetics