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Field
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reliability. · Understanding of hardware accelerators for AI and their operation. · Familiarity with machine learning workloads (e.g., CNNs). As this is a research position, it is necessary
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. Research Responsibilities Responsibilities will vary depending on the Fellow’s background, but may include: • Developing machine learning, optimization, or simulation models to improve clinical operations
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standard Python libraries for machine learning, in particular PyTorch. Website for additional job details https://emploi.cnrs.fr/Offres/CDD/UMR6072-DAVTSC-008/Default.aspx Work Location(s) Number of offers
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job description A central challenge in machine learning is ensuring
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and societal. In this context, we welcome applicants from diverse backgrounds such as computer science, electrical and computer engineering, sociology, public policy, information science, communication
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microbiology, and machine learning, you will identify AMR genes, pathogens of public health concern (including ESKAPE and WHO-priority organisms), and reconstruct metagenome-assembled genomes (MAGs). Across five
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, applications of machine learning to particle phenomenology, and lattice QCD, both within the Standard Model and beyond. The particle physics phenomenology group members are: J. F. Kamenik (head), B. Bajc, S
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Location: Kavli Institute for Nanoscience Discovery Contract type: 1 year Fixed-term (with the possibility of an extension) We are seeking a Postdoctoral Research Assistant for the Gene Machines
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Responsibilities will vary depending on the Fellow’s background, but may include: Developing machine learning, optimization, or simulation models to improve clinical operations and resource allocation Advancing
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written), time management, project management, and presentation skills Proficient with computer applications and programs associated with the position (i.e. Microsoft Office suite) Strong attention