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sciences Collaboration with experts in lab science, medicine, and machine learning Modern GPU compute infrastructure A chance to contribute to cutting-edge research with real-world impact Who you are Strong
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and GPU-accelerated computing. Familiarity with job scheduling (e.g. SLURM), conda/mamba environment management, and pipeline orchestration (e.g. Snakemake) is required. have strong proficiency in
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processing, computer vision, machine learning, deep learning and neural networks, as well as courses in python, GPU programming, mathematical modeling and statistics, or equivalent. The University may permit
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– Documented experience in large-scale data management, high-performance computing systems, GPU acceleration, and parallel file systems – Ability to communicate fluently in English, both spoken and written
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School of Electrical Engineering and Computer Science at KTH Project description Third-cycle subject: Computer science This project involves generative modeling to address missingness in mass