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an email to science.recruitment@uu.nl . Website for additional job details https://www.academictransfer.com/357312/ Work Location(s) Number of offers available1Company/InstituteUniversiteit
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) Positions PhD Positions Country Italy Application Deadline 15 Dec 2025 - 12:00 (Europe/Rome) Type of Contract Other Type of Contract Extra Information Scholarships Job Status Full-time Is the job funded
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employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/ This is a joint PhD position with the Umeå Centre for Gender Studies
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | 18 days ago
the Inria-AIO team (https://team.inria.fr/aio/ ) and will receive their PhD from Sorbonne University. The Inria-Paris center is located at the heart of Paris, in the 13th arrondissement. Some details of
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Externally Funded PhD with Fulham FC Department Graduate School Location London Post Type Full Time Closing Date Friday 16 January 2026 Reference EHPHD12-25 About the Opportunity This is an
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. Cell, 173 (7): 1622-1635. For more information, visit https://www.timmslab.com For further details or informal enquiries, please contact Richard Timms via email (rtt20@cam.ac.uk ). Fixed-term: The funds
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Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications -PhD degree in the year of employment in the project or within 7 years before 1 January of the year ef employment in the project
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phenomenology is anticipated. Where to apply E-mail jobs@ifj.edu.pl Requirements Research FieldPhysicsEducation LevelPhD or equivalent Skills/Qualifications -PhD degree in the year of employment in the project
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material, as well as a work-plan. Please see the CBS website for more information about admission here: https://www.cbs.dk/en/research/phd-cbs In addition to the research proposal, the application must
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SD- 26053 PHD IN ULTRA-FAST MACHINE-LEARNING INTERATOMIC POTENTIALS FOR NANOINDENTATION OF TIC MA...
PhD candidate to develop and apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular