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individuals and patients. These projects involve large-scale neuroimaging data collection at 3T and 7T, computational modeling of brain responses using machine learning methods, and cross-institutional clinical
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methodologically strong and motivated to work at the intersection of applied machine learning, social sciences, and natural sciences. Essential qualifications: A completed PhD in data science, computer
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management. Learn more about why Lund University might be the right choice for you here , and more about working in Sweden here . These films will also give you more information about Working in Lund
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-performance computing resources suitable for large-scale machine-learning and foundation-model experiments. Your role We are seeking a highly motivated Postdoctoral Researcher to join the FNR AI-HPC 2025
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presentations, and the drafting of the dissertation. The program's primary goal is to prepare candidates for a career in international academe. For further information about the PhD program, please visit https
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 16 hours ago
is also leading the development and validation of novel machine learning methods for LEGEND simulations and analysis. We have been heavily involved in constructing, commissioning, and operating
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is accomplished primarily through activities of the Bureau of Business and Economics Research. Additional information about the School and its programs can be found at LSBE’s website at http
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LevelMaster Degree or equivalent Skills/Qualifications We are looking for an ambitious PhD candidate with the following requirements: 1. Data Integration and Management Ability to compile and harmonize large
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outcomes of therapy. The lab is looking for candidates for the following two stipends: • Stipend 1: Computer Vision-Based Analysis of Humans. This PhD candidate will focus on developing new AI/computer
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: Investigate and design optimal computing and communication architectures for hardware acceleration of large-scale machine learning workloads Perform characterization and modeling of electronic and optical