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Field
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to connect the Departments of Physics and Astronomy, Computer Science, and Mathematics. This initiative includes a dedicated interdisciplinary space for future faculty, postdocs, and students, as
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FieldMathematicsYears of Research ExperienceNone Additional Information Eligibility criteria Academic: PhD in applied mathematics, computer science, or medical physics. Scientific interests: applied mathematics
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University of Warsaw: Faculty of Mathematics, Informatics and Mechanics | Poland | about 1 month ago
21 Aug 2025 Job Information Organisation/Company University of Warsaw: Faculty of Mathematics, Informatics and Mechanics Research Field Computer science Mathematics Researcher Profile Recognised
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essential that you hold a PhD/DPhil (or close to completion) in mathematics, computational biology, data science, statistics, physics, or a related discipline, and have experience of analysing and
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activities. You will have: a PhD in an area relevant to the project, like biology, physics, applied mathematics previous experience with computational modelling, method development, and numerical analysis
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research environment at the heart of the Delft University campus. Our team values diversity and fosters an inclusive, international culture. Requirements PhD in physics, quantum information
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4 Sep 2025 Job Information Organisation/Company Fundación IMDEA Nanociencia Research Field Physics » Mathematical physics Researcher Profile Recognised Researcher (R2) Positions PhD Positions
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Deadline 25 Oct 2025 - 00:00 (UTC) Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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has: a PhD in a related or relevant field to this project design and conduct experiments collect and analyse data, including with the use of machine learning develop mathematical models of excavation