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should have, or be expecting soon to receive, a PhD in Mathematics, or related field, with demonstrated research experience in the mathematical foundations of AI, as well as substantial programming
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of the findings and ensure they can inform policy and practice. You will have a PhD or equivalent professional qualification in statistics or epidemiology, and experience or an interest in medical
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of Engineering and Applied Sciences. The fellow will design and run human experiments, perform data analysis, and create computational models of learning and memory. A PhD is required. An ideal candidate will be
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for recent PhD graduates to establish independent research careers. These 6-month fellowships (October 2025 - March 2026) offer a crucial bridge for promising researchers to develop their careers while
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Pay Grade/Pay Range: Minimum: $48,600 - Midpoint: $60,800 (Salaried E7) Department/Organization: 214241 - Computer Science Normal Work Schedule: Monday - Friday 8:00am to 5:00pm Job Summary: The
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and presenting Job Requirements: PhD degree in Artificial Intelligence, Computer Science, Software Engineering Strong background and research experience in artificial intelligence, software engineering
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for interdisciplinary collaborations. The position additionally offers travel support for conferences and meetings and a monthly housing allowance. Qualifications • Qualifications/ Discipline: PhD in Physics, Data
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/despacho_8532_regulamento_bolsas.pdf Workplace: The work will be carried out at the Library of Instituto Superior Técnico (Campus Alameda), under the scientific guidance of PhD Isabel Pacheco Marques Vaz Marcos Website for additional
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towards this goal. The PhD research fellow will be part of the PhD programme in Computer Science: Software Engineering, Sensor Networks and Engineering Computing (https://www.hvl.no/en/research/phd
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will need good communication skills, and will be able to work with and disseminate information to both academic and non-academic audiences. You will have a PhD in medical or bio-informatics, epidemiology