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research programme Access to secure clinical and multi-omics data environments Modern GPU, and high-performance computing resources, plus dedicated research-engineering support Close integration with
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. Programming & Software Development: Proficiency in Python, PyTorch, JAX, or other ML frameworks Computing: Some experience with large-scale datasets, parallel computing, and GPUs/TPUs. Algorithm Development
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for accelerators, such as GPUs or FPGAs. Experience in refactoring or porting large codebases (over 100k source lines of code). Background in supporting scientific code on HPC systems or familiarity with components
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with edge computing or embedded systems (e.g., NVIDIA Jetson, Raspberry Pi) Background in real-time processing and GPU acceleration (CUDA) Participation in relevant competitions (e.g., Kaggle, computer
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good understanding of the physics of scattering and antenna radiation Programming experience in C/C++ is necessary while experience in parallel and GPU computing is most desired More Information Location
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. Key attractions are access to a high-performance computing cluster (GPU/CPU and more than 300TB of data), two 3T Prisma MR scanners, and an MR compatible digital EEG system as well as collaboration