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Knowledge of deep learning architectures, graph neural networks, or uncertainty quantification Familiarity with HPC environments Language Requirements: Applicants must demonstrate at least B2-level
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working language Training at a strong medical research university (MUI) with access to HPC, expert bioinformatics mentorship, and close experimental collaborations A project with clear scientific novelty
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HPC systems Practical experience working with conda environments and Python scripting Motivation to contribute to the development of an open-source molecular modeling platform for soil components Hands
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(MUI) with access to HPC, expert bioinformatics mentorship, and close experimental collaborations A project with clear scientific novelty, real translational relevance, and multiple publishable
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is 4 years. The PhD candidate will join COMPSOIL, a dynamic and international research environment, benefiting from the University's high-performance computing (HPC) infrastructure and opportunities
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publications at top-tier venues such as CVPR, ICCV, ECCV, NeurIPS or ICRA. You will have access to extensive compute resources at TU Delft, ranging from local GPU servers to large-scale HPC infrastructure
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; additional experience in one or more of the following areas is highly desirable: stochastic simulations quantitative genetics breeding programs working with Linux and HPC systems For this position your command
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is highly desirable: big data analytics quantitative genetics variance component estimation working with Linux and HPC systems For this position your command of the English language is expected to be
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skills in Python and/or R; experience with Linux/HPC environments is an advantage Experience with genomic data analysis, high-performance computing, GPU programming, or software development is a plus
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dissipate higher heat loads from HPC and AI data centers but still require additional air-cooling support for other components, to ensure the efficiency of these systems. To overcome these limitations