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Are you interested in exploring how multi-agent aerial manipulation can contribute to construction and working at the intersection of robotics and machine learning? Job description Advancements in
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of machine learning and clinical oncology, with access to a large multimodal research dataset, substantial GPU resources, and a collaborative scientific environment. Your tasks Design and implement LLM-based
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Eligibility Criteria You must have, or expect to achieve, at least a 2:1 Honours degree in biology, genetics, biomedicine, or a related area. The candidate must be willing to learn bioinformatics. A further
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Honours degree in biology, genetics, biomedicine, or a related area. The candidate must be willing to learn bioinformatics. A further qualification such as an MRes is advantageous. The studentship covers
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
athletic programs, Carolina is an ideal place to teach, work and learn. One of the best college towns and best places to live in the United States, Chapel Hill has diverse social, cultural, recreation and
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. Together we will draw up a career plan that includes the skills and knowledge you will acquire An inclusive working environment with ambitious colleagues The opportunity to take Norwegian language courses
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development work at the Norwegian University of Science and Technology (NTNU) for general criteria for the position. Preferred selection criteria Experience with machine learning and neural networks Basic
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how AI is changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across
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changing work. Its projects examine what happens when generative and agentic AI enters leadership, everyday workflows, team communication, professional learning and career decisions. Across the network