442 computational-physics-"https:"-"https:"-"https:"-"https:"-"IFM" Fellowship positions in United Kingdom
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- VIN UNIVERSITY
- York St John University
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to make a meaningful impact? Mathematics & Computer Science - Postdoc Fellows E-STEEM Call 2026 174 Research Services and Career Development Startdate: 01.10.2026 | Working hours: 40 | Collective bargaining
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that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to deliver on a Pharmaceutical Innovation Programme Singapore research project where you
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You will join our team at the Optoelectronics Research Centre and work on the Engineering and Physical Sciences Research Council funded project HyMeta: Hyperuniform Disordered Metasurfaces
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industrial partners. The role will focus on developing advanced physics-based continuum models for sodium-ion batteries, with particular emphasis on hard carbon anodes and phase-changing layered oxide cathodes
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ABOUT VINUNIVERSITY’S RESEARCHER 200 VinUniversity is proud to launch the RESEARCHER200 Program, designed to attract exceptional researchers from around the world to join our vibrant research
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You will join our team at the Optoelectronics Research Centre and work on the Engineering and Physical Sciences Research Council funded project HyMeta: Hyperuniform Disordered Metasurfaces
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experience and a keen interest in developing physics and chemistry tools to reveal complex protein/glycan interactions? Are you eager to develop your expertise, push the boundaries of knowledge, and pursue a
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experience and a keen interest in developing physics and chemistry tools to reveal complex protein/glycan interactions? Are you eager to develop your expertise, push the boundaries of knowledge, and pursue a
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School of Physics and Astronomy. You will carry out a research programme analysing stellar populations and chemical enrichment processes in galaxies using large galaxy surveys such as SDSS and DESI, as
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analytical backbone of the programme. It develops sensor-enabled diagnostic cells, multi-modal data pipelines and hybrid physics-informed machine learning approaches to understand interfacial behaviour during