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. Neuromorphic computing and ML deployment on digital and neuromorphic processors TinyML and EdgeAI and ultra-low-power inference for resource-constrained systems Techniques such as quantization, pruning
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apply bioinformatics and statistical genomics approaches to characterize trait-associated sequence variation. We offer two PhD positions at the interface of computational and statistical genomics, and
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. The position is subjected to admission to the doctoral program at D-MAVT. Profile We are looking for : a curious and resourceful individual, with a pronounced taste for interdisciplinary science, experimental
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Master’s degree in Computer Science, AI, Machine Learning, Mathematics, Electrical Engineering, or a closely related field; or Master’s degree in Medicine (MD) with strong Python skills and some ML
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have enabled unprecedented control over light-matter interactions, catalyzing breakthroughs in imaging, nonlinear optics, and photonic computing. We leverage these developments to advance the field
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of Competence in Research (NCCR) Separations. Job description Within a broader research program that integrates process modelling, computational materials screening and discovery, experimental synthesis, and
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the power of both classical and quantum computing resources? How can we exploit or take inspiration from quantum physics to develop cutting-edge machine learning? Your work will encompass a diverse array of
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80%-100%, Lugano, fixed-term The Swiss National Supercomputing Centre (CSCS) develops and operates a high-performance computing and data research infrastructure that supports world-class science in
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, Computer Science, Applied Mathematics, or a field focused on the intersection of Machine Learning and Optimization Proven expertise in surrogate modelling, specifically in designing neural architectures
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novel research programme at the frontier of multimodal AI and ICU clinical cognition. Under the guidance of Prof. Jutzeler, a dedicated postdoctoral researcher, and collaborators, you will have access