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live in. Your role Since 2006, the University of Luxembourg has invested in its own High-Performance Computing (HPC) facilities. Special focus was laid on developing large computing power combined with
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. outside of HPC environments) Downloading a copy of our Job Description Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided
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people from non-technical backgrounds Experience with developing or deploying light weight models in environments with restricted resources (e.g. outside of HPC environments) Downloading a copy of our Job
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months or 0.8 FTE for 45 months; access to computational resources (HPC), GIS/data infrastructure, and datasets via collaborative networks; a supportive, interdisciplinary research environment within
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HPC environments Good communication skills to interact with collaborators ranging from machine learning researchers to pathologists or medical students Knowledge of biology and medicine is a plus Highly
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yield optimization. Exposure to quantum chemistry (DFT) and molecular simulations is a plus. Experience with cloud computing and/or high-performance computing (HPC) resources. Application Process
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modeling. Perform predictive modeling using high-performance computing (HPC) infrastructure. Validate computational predictions by collaborating with experimental groups conducting reverse genetics studies
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with high-performance computing (HPC) infrastructures is advantageous Excellent analytical and problem-solving capabilities Proven track record of publishing in reputable scientific journals and at
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
, large-scale AI, generative AI, and Exascale HPC to detect, quantify, and characterize key parameters of the global carbon cycle at high spatial resolution with a focus on above and below ground
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discipline. Demonstrated hands-on experience and understanding of developing and applying HPC algorithms to sparse numerical, scientific and ML models. Demonstrated research experience with AI and ML