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Details Title Postdoctoral Research Fellow School Harvard Medical School Department/Area Immunology Position Description We invite applicants for a postdoctoral fellow position in the von Andrian
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characterization, scientific computing, and artificial intelligence. Applicants should have: A Ph.D. in mechanical engineering, materials science and engineering, applied physics, computational science, or a closely
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, delay thermal breakthrough, and enhance long-term thermal recovery from EGS. This position also aims to model, evaluate, and optimize innovative engineering solutions, including chemical, mechanical
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, shaping the future of medicine through cutting-edge research. We are seeking a highly motivated and creative Postdoctoral Fellow to join our multidisciplinary research program investigating the molecular
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Research Framework Programme? Other EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Position identification Title of post : Postdoctoral Research
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(e.g. Textile or Materials Science, Chemistry, Agricultural or Mechanical Engineering or a closely related field). Preferred skills: Experience and knowledge with property measurement and processing
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Deadline 20 Sep 2026 - 00:00 (UTC) Country Australia Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related
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condition that the person who accepts the position applies for and is granted admission to the Faculty’s PhD-program in Technology within three months of starting in the position. The doctoral programme
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University of British Columbia Department of Surgery | Northern British Columbia Fort Nelson, British Columbia | Canada | 2 months ago
biology and gene engineering approaches Developing in vivo strategies to generate antigen-specific Tregs using targeted delivery technologies, including lipid nanoparticles Discovering novel mechanisms by
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computation, including surrogate models, efficient proposal mechanisms, and learned transport maps. • Analyse the mathematical properties of proposed algorithms, including convergence and ergodicity where