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Uppsala University, Disciplinary Domain of Science and Technology, Faculty of Mathematics and Computer Science, Department of Information Technology Are you interested in working with machine
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 14 days ago
opportunity? Please email [email protected] Qualifications The candidate should have a PhD in Mechanical Engineering, Aerospace Engineering, Materials Science and Engineering, or a related technical discipline. The
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plan experiments carried out by technical staff (BTS/DUT level) and/or engineers and Master’s students involved in the project Use specialized software tools for bibliographic research, reference
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fostering a respectful workplace – in how we treat one another, work together, and measure success. Basic Qualifications: A PhD in mechanical engineering, computer science, or a related field completed within
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to the project): PhD in Computer Science, Distributed Software Architectures, Artificial Intelligence, or a related discipline. Strong research background in data management, including policy governance or data
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porous-silicon experience is advantageous but is not essential where a candidate brings strong adjacent expertise at the engineering-biology interface. Essential criteria A PhD awarded, or thesis submitted
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/or software engineering are recommended for this position. The post requires strong research, programming, and system development abilities. Applicants must have a track record of publications in
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, including through the wider Amsterdam quantum ecosystem; taking a leading role in scientific publications, open and reusable research software, presentations and/or knowledge-transfer activities; helping
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others and contribute to a team environment. Technical Proficiency: Skilled in using office software, technology, and relevant computer applications. Communication: Strong and clear written and verbal
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-learning architectures for sequential data (e.g., Transformers, graph neural networks, state-space models). Experience with OpenCV, GPU-accelerated inference, Docker, and modern software engineering