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Field
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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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and GPU servers for the delivery of the PC exercises, and jointly supervising the PC exercises during the course What you contribute Student on a STEM degree programme Good knowledge of at least one of
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Job Description Field of Research: Computational biology/bioinformatics with emphasis on spatial transcriptomics, proteomics, and immunosequencing using Pixel‑seq and an immune receptor‑focused
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of the art equipment within DNA and RNA sequencing, laboratory automation, CPU and GPU compute resources, proteomics, metabolomics, and advanced microscopy. This position offers an excellent opportunity
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learning architectures for scientific or high-performance computing applications. Background in software performance evaluation, profiling, and optimization on CPUs and GPUs. Knowledge of common numerical
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computing, electronic, fabricating, testing, printing, and word processing. High speed computing facilities are available at the National Supercomputing Center for Energy and the Environment hosted in
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. Due to the interdisciplinary nature of the work, we are looking for a person with a background in performance engineering and high-performance computing hardware (high-performance CPUs and GPUs) as well
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geophysical sciences, computer science, or machine learning with 0 to 2 years of experience Knowledge of deep learning, PyTorch/JAX, and scaling deep learning models to large GPU-based machines Technical
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program embedded in a large-scale, nationally funded research consortium with access to unique multimodal clinical datasets - State-of-the-art GPU infrastructure for training and fine-tuning large
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). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications Experience with multi-GPU model training and large-scale inference. Familiarity with modern AI