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interdisciplinary team spanning statistics, machine learning, genetics, and population health. You will work closely with collaborators at the Nuffield Department of Population Health (NDPH), the Big Data Institute
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hold an MSc in Earth science, environmental science, data science, physics, mathematics or computer science, with practical machine learning/artificial intelligence courses and relevant project and
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within SCI and across other departments within Pitt, and initiatives like the $11.6M Western Pennsylvania Quantum Information Core (https://www.pitt.edu/pittwire/features-articles/pitt-investment-pa
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 5 hours ago
approaches, machine learning methods) to clinical, biological, and patient reported data. Collaborate with investigators to interpret findings, prepare manuscripts, and disseminate results through peer
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. You will become part of a dynamic, collaborative working environment with expertise in drilling engineering, geomechanics, machine learning, and energy systems. The project will integrate real‑time
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for a dedicated PhD student to join our team. Find more information about the Strategic Management area and its members here: http://strategy.univie.ac.at What you will be doing: In
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information, quantum technologies and machine learning. Internal further training & coaching: The Vienna Doctoral School as well as the Department of Human Resources offer plenty of opportunities to grow your
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for the university and funding agencies. Job Requirements: PhD qualification degree in Computer, Electrical or Electronic Engineering or related field At least 3 years of relevant research experience in AI security
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of Computer and Information Science , within Linköping University . Your work assignments As a PhD student, you devote most of your time to doctoral studies and the research projects of which you are part. Your
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Machine Learning; (ii) Big Data and Data Management; (iii) Computer Vision and Pattern Recognition; and (iv) Distributed Systems and Networking. These key research areas have a special thematic focus on (a