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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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/ machine learning algorithms to support research in the IDMxS Analytics Cluster. The RF will apply/ improve machine learning algorithms to process (e.g., classify, predict) data collected by IDMxS. Help
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or theoretical/computational physics. Master’s students may apply if they expect to complete their final examination by 01.10.2025. Employment is contingent upon the degree being awarded. Solid experience with
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to invite applications for the KICP Postdoctoral Research Fellowship program. Scientists receiving a PhD in physics, astrophysics, astronomy, or related fields between June 2022 and September 2026 are welcome
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geophysics or a closely related field such as applied mathematics or theoretical/computational physics. Master’s students may apply if they expect to complete their final examination by 01.10.2025. Employment
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, along with an aptitude for developing new experimental techniques that relate to this exciting research program. To be successful with your application, you will need to demonstrate: An awarded PhD in
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PhD Research Fellow in Chemistry-focus on Experiments in Chemical Kinetics and Heterogeneous Catalys
oppdatert 02.08.2025 Hva er en cookie? En cookie er en liten datafil som lagres på datamaskinen, nettbrettet eller mobiltelefonen din. En cookie er ikke et program som kan inneholde skadelige programmer eller
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training programme or within 4 years full-time equivalent of completing their training programme are eligible to apply. Clinical work during the PhD will be limited to one day per week. Doctors and dentists
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We are seeking a Research Fellow to perform research on deployment of machine-learned models for health analytics on distributed IoT/edge/cloud systems using transprecise computing and contribute
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Computer Science, Mathematics, Physics, Applied Economics, or a related quantitative field. Skills and Knowledge: Knowledge of scientific computing, data assimilation, and machine learning frameworks. Proficiency in