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University of California, San Francisco | San Francisco, California | United States | about 2 months ago
, including total compensation, please visit: https://ucnet.universityofcalifornia.edu/compensation-and-benefits/index.html Department Description This position is within the Division of Cardiology at San
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(HPC). • Experience with machine learning and network biology. • Background in cancer research. Pay Range: $62,232.00 - $81,000.00 To apply visit https://academicjobsonline.org/ajo/jobs/31509 and submit
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Center for Advanced Systems Understanding, Helmholtz Center Dresden-Rossendorf | Germany | 3 months ago
Computing (HPC) cluster environments and the Slurm cluster environment is required Communication skills in English and in a professional context (presentation of research results at scientific meetings
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energy efficiency during the training process and (ii) science yield (sensitivity / resolution) during inference. A key aspect is to benefit from hybrid HPC + AI approaches within the workflows
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Systems, High-Performance Computing, and Augmented/Virtual Reality are of particular interest. Detailed Position Information The Department of Computer Science (CS: https://cs.ua.edu/ ) and the Lee J
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coastal hub. Read more about working at Chalmers and our benefits for employees. AIMLeNS offers: Access to state of the art HPC computing facilities (BerzeLiUs, Alvis) Mentorship for career development
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familiarity with high-performance computing (HPC) are required. At the University of Michigan School for Environment and Sustainability (SEAS), we are at the forefront of building a more sustainable and just
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benchmarking of large language models (LLMs). The research profile of the group is heavily machine-learning oriented and the group has access to excellent HPC infrastructure. For more information about LTG
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for scientific discovery; integration of HPC and AI and AI-enhanced numerical methods; explainable and trustworthy AI for STEM applications; and mathematically grounded approaches applied in STEM contexts, such as
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AI, or active learning for materials applications. Integration of theory and experiment: Using computation and ML to interpret or guide experimental work. High-performance computing (HPC) and data