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mission utilizing the expertise, resources, and capabilities available at your hosting facility. You will acquire experience and training in areas related to fusion energy and plasma science and technology
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computing and machine learning. The research will emphasize both theoretical advancements and practical implementations optimized for modern HPC systems. The postdoc will primarily contribute to one or more
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experience with software radios, 5G user equipment, VPNs, Tor, or other hard- and software relevant to the described systems an networks Up-to-date software development and machine learning skills, incl. work
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Oxford’s Department of Orthopaedics (NDORMS) as well as collaborators in Bristol and Cardiff. You should have a PhD/DPhil (or be near completion) in robotics, computer vision, machine learning or a closely
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of Science at UvA. What are you going to do? The aim of the project is to use advanced Machine Learning techniques to predict the anharmonic vibrational spectra of large Polycyclic Aromatic Hydrocarbon (PAH
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familiarity in machine learning (ML) and artificial intelligence (AI). This role is pivotal in evaluating the economic competitiveness of the U.S. in the production and manufacturing of energy-related materials
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of manuscripts, presentations, conferences, and grants. Preferred Qualifications Equipment Utilized Physical Demands and Work Environment Overview Candidates must be highly motivated, open to learning new
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Technology Enabling Advanced Drone- Facilitated Active Support Tactics for Military and First Responder Operations.” You will be a member of the Human-Robot Collaboration Lab and Learning & Autonomous Control
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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Current Employees: If you are a current Staff, Faculty or Temporary employee at the University of Miami, please click here to log in to Workday to use the internal application process. To learn how