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expertise to enable real-time sequence analysis and deliver clinically actionable results within hours. Job description You will develop and implement novel computational methods for the analysis of long-read
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, Switzerland [map ] Subject Areas: Computer Science / Distributed Systems and Networking , Networking , Networking and distributed systems Appl Deadline: 2026/01/08 11:59PM (posted 2025/11/10, listed until
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engineering Strong background in computational science, applied mathematics, or computational biology Ideally, familiarity with numerical methods for PDEs (e.g., finite difference, finite element) HPC
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thinking with a structured, quality-focused approach to data and methods. Ideally, experience in one or more of the following: data engineering, building data-driven apps, computational linguistics, machine
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models Lead the design and implementation of innovative methods, which could include but are not limited to: Kriging surrogate, Polynomial Chaos Expansion (PCE), and Physics-Informed Neural Networks (PINNs
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degree in biomedical engineering, mechanical engineering or related relevant field A demonstrated and substantial experience with computational simulation methods, i.e. finite element analysis English
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80%-100%, Zurich, 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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of computer graphics fundamentals, numerical methods, and GPU/parallel computing concepts. Experience with at least one major deep learning framework (PyTorch preferred). Excellent problem-solving skills and
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of emerging technologies balanced against their dark sides. Our research at the intersection of data, behavioural, and computer science draws on data from real-world and experimental settings The Centre for AI
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ISSAC Newton, or Mujoco Good foundation in linear algebra, numerical methods, optimization, and control theory. An excellent knowledge (written/oral) of English is a must. Knowledge of German is