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Bernardino de Almeida, 400Geofield Contact State/Province Porto City Porto Website https://www.ess.ipp.pt/ Street Rua Dr. António Bernardino de Almeida, 400 Postal Code 4200-072 E-Mail geral@ess.ipp.pt Phone
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website (https://www.nottingham.edu.cn/en/humanities-and-social-sciences/schools-and-department/international-studies/home.aspx ) For research proposal discussion, please contact Dr Rosaria FRANCO
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with producing rAAV and brings together experts from two leading Irish institutions, NIBRT and UCD, and APC-VLE Ltd. (https://approcess.com/services/cell-and-gene-therapies ) - a leading Irish industrial
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: Institute of Social Sciences of the University of Lisbon. Scientific Orientation: The grant holder will be supervised by Dr Roberto Falanga, the project coordinator. Duration of the grant: The grant will last
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Resalati Supervisors: Dr Aydin Azizi Contact: Prof Shahab Resalati (sresalati@brookes.ac.uk) Entry requirements: Essential Criteria A Master’s degree (or equivalent) in Electrical Engineering, Control
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the Doctoral School of Energy, Materials, Earth and Universe Sciences. The ANR CHAIN-H2 AAPG2025 – CES 05 project brings together a consortium comprising the French Nuclear Safety and Radiation Protection
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Research Assistant or Associate in Operator Algebras to work with Dr Chris Bruce in the School of Mathematics, Statistics and Physics at Newcastle University. This position is full time for a duration of 24
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Institute of Low Temperature and Structure Research Polish Academy of Sciences | Poland | 17 days ago
to the Doctoral School of ILT&SR PAS https://phd.intibs.pl/files/dokumenty_EN/25-04-29-Zasady_rekrutacji_SD_INTiBS_PAN_en.pdf Description of the research project and the PhD thesis The proposed doctoral project
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by PI Dr. Jessica Hsu (starting January 2026), is seeking highly motivated and creative postdoctoral fellows to join a research program that integrates molecular imaging and nanomedicine, leveraging
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next-generation machine learning (ML) models that are both data-efficient and transferable, enabling more reliable catastrophic risk prediction, defined as the probability of exceeding critical safety