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models, LLMs and Transformer architectures Excellent programming skills in PyTorch/JAX and experience working with GPUs and high-performance clusters. Strong mathematical skills with excellent
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to clinical data; design interpretable representation spaces for tumor-immune dynamics and therapy response. Technical Expertise (25%) – Engineer LLM and diffusion/flow-matching pipelines; integrate multi-GPU
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learning, multicore and GPU programming, and highly parallel systems. Good knowledge in one or more of the following programming languages/environments: C/C++, Python, PyTorch (or similar), and Cuda. Place
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will benefit from the Jean Zay supercomputer to perform intensive GPU calculations but also MARBEC/LIRMM GPU shared resources (https://umr-marbec.fr/recherche/dispositifs-de-recherche/den/ ). His/her
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funded by the EU FP7 program, H2020 program and the European Space Agency (ESA). For further information, you may check: www.securityandtrust.lu The SigCom research group carries out research activities in
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for certain posts On-Site nursery On-site gym Enhanced maternity, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance Visit https://www.ucl.ac.uk/work
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programme Reference Number AE2025-0506 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt/editais/pt/AE2025-0506
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description What you will do We are seeking an experienced and visionary System
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of automation systems for software deployment, configuration management, CI/CD, and environment lifecycle processes. Partner with researchers and domain experts to optimize applications for CPU/GPU architectures
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Computational Imaging Research Lab (CIR), Department of Biomedical Imaging and Image-guided Therapy | Austria | about 1 month ago
reference letters have been received in the system. Further details, including the FAQ and Application Guide, are available at: https://www.meduniwien.ac.at/web/en/studierende/mein-studium/phd-programme-un094