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Field
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relevant programming frameworks Advanced programming skills in relevant programming languages and contexts (e.g., Python, HPC/GPU programming, big data applications) Strong team spirit and experience in
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computational resources (with GPUs) A collaborative environment across research fields, including plant biology, quantitative genetics, and population genetics Opportunities for collaboration and research visits
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networks, RNNs, LLMs) or in the deployment of such algorithms. Experience with specialized computational architectures such as GPUs, FPGAs, neuromorphic processors, or machine learning accelerators
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will be viewed highly favorably. Experience with GPU acceleration or code parallelization paradigms (e.g., MPI, OpenMP, CUDA). FLSA Exempt Full Time/Part Time Full Time Number of Hours Worked per Week 40
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Interest & knowledge about oncology & immunology, molecular & cellular mechanisms Work with ML + generative AI + GPUs at scale Experience with clinical or biomedical data and workflows Enjoy multimodal
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). Resources: Access to a project-dedicated H200 GPU cluster, travel funding for top-tier conferences, and the broader compute resources of the Vector Institute/Digital Research Alliance of Canada. How to Apply
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atmospheric modeling, artificial intelligence, and near real-time applications. The successful candidates will contribute to the development of high-performance and GPU-enabled modeling tools for wildfire
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at the interface of AI, imaging, microbiome research, and laboratory automation within a Helmholtz-wide collaboration. Access to state-of-the-art live-cell imaging, microfluidics, laboratory automation, and GPU
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optimization Familiarity with continuous-variable/bosonic systems, non-Gaussian states, multimode entanglement, or Wigner-function methods Experience with HPC workflows (cluster computing, GPU computing
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programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs