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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
translation models and medical images analysis are considered important assets. Established expertise in key machine & deep learning frameworks and toolsets. Experience in GPU computing, HPC, Containers & Image
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/ computer vision and pattern recognition, including but not limited to biomedical applications Strong interest in applied machine learning, including but not limited to deep learning Experience utilising GPU
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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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l'institut du thorax, INSERM, CNRS, Nantes Université | Nantes, Pays de la Loire | France | about 7 hours ago
Devices" ). • Bring various improvements on the synthetic model (vasculature shape / aneurysm / background noise modelling) • Numerical simulations will be performed on a GPU HPC cluster. • Programming in
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typically work with datasets of up to several TBs depending on the case study); - Autonomy to conduct independent analysis and research on our (GPU/CPU) servers, familiarity with coding frames in machine
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-dependent approaches. -Proficiency in high-performance computing (MPI/OpenMP/GPU) and scientific code development is a plus. -Interest in attoscience and/or matter–antimatter physics is an asset. -Ability
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-getalp.imag.fr/ ), which offers a dynamic, international, and stimulating environment to conduct high-level multidisciplinary research. The person will have access to large datasets, GPU servers, means
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scientific computing. You are proficient in several languages (Python, C/C++, or Fortran), with extensive knowledge in AI/ML and parallel programming (GPU, multi-threading, etc.). You have strong software