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working on related topics Participate in teaching and supervision activities, in line with the candidate's profile and interests The research activities will be hosted by the Parallel Computing and
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simulation environments and real-world deployments with the nano-drones of the University's SwarmLab The research activities will be hosted by the Parallel Computing and Optimisation Group (PCOG) at SnT
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disease prognosis. This position offers a unique opportunity to work at the forefront of optical imaging technology, combining experimental optics with advanced computational and data-driven methods. Roles
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on competence: contributing to research software development supporting simulations and/or data workflows (HPC/parallel environments), and open/reproducible release of data and analysis scripts under FAIR
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reconstruction methods (e.g., Born/Rytov approximations, multislice or multiple-scattering models). Proven experience in scientific programming and numerical computing (MATLAB, Python, or C/C++), including
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate
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, you’ll join a technically driven, publication active team known for research in computational modelling, CFD, numerical methods and high-performance computing, with a strong culture of code quality, open
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modern high performance computation facilities and parallel computing clusters (CPU and GPU). Excellent publication record and demonstrated conference presentation skills. Demonstrated ability to operate
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hired at BTH will mainly focus on two aspects of neuromorphic computing: Guidelines / frameworks for mapping applications to neuromorphic systems. Efficient training methods of neuromorphic applications