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Field
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7 Apr 2026 Job Information Organisation/Company UNIVERSITY OF SOUTHAMPTON Research Field Computer science Physics Researcher Profile First Stage Researcher (R1) Application Deadline 20 Apr 2026 - 00
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of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects
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applications for the innovative frameworks and designs developed in the programme Manage the project timeline and collaborate with other research staff to address technical challenges. Regularly report progress
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for Aumovio through close collaboration with its business units. This research position is related to Project C3 “Communication over In-Vehicle Powerline” of the Aumovio-NTU corporate lab Phase 2 program. We
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focused on the optimal utilisation of advanced RF sensors that are capable of performing multiple roles, either sequentially or in parallel. The UCL Radar Group hosts one of the few demonstrator systems
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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Responsibilities: Develop and optimize flexible electronic devices, including sensors, actuators, and integrated circuits for health monitoring / wearable robotics applications. Design and fabricate flexible
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12 Mar 2026 Job Information Organisation/Company LNEC, I.P. Department Human Resources and Facilities Services Research Field Computer science Researcher Profile First Stage Researcher (R1
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 14 days ago
. Non-U.S. citizen applicants should refer to the Guidelines for Non-U.S. Citizens Details page of the program website for information about the valid immigration statuses that are acceptable for program
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machine learning methods for computational materials physics and chemistry. Projects include: The aim is to develop generalized equivariant neural network models NequIP and Allegro for machine learned