3,083 evolution "https:" "https:" "https:" "https:" "https:" "https:" "Queen Mary University of London" PhD positions
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process & fluid optimization -- Development of a multi-objective optimization methodology to simultaneously determine the optimal cycle architecture, its operating parameters, and the most suitable working
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will receive 30 days of vacation KNOWLEDGE & DEVELOPMENT: Your professional development is important to us – we support you specifically and individually e.g., through training and networking
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funded through the EU Research Framework Programme? Horizon Europe - ERC Reference Number 1227.1101.49.2026 Is the Job related to staff position within a Research Infrastructure? No Offer Description https
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partners specialized in the synthesis of POSS cages, the characterization of porous materials, and molecular modeling. The reduction of carbon dioxide (CO₂) emissions and the development of clean energy
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considered for funding at a later stage in the recruitment process. Further details about eligibility and funding can be found at: https://www.ukri.org/councils/esrc/career-and-skills-development/funding
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applications for the position of Research Assistant in Invasive Pest Genomics. The intern will contribute to the efforts of an NSF-funded project (https://www.nsf.gov/awardsearch/showAward?AWD_ID=2418203
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congested architectures. For more information, visit my professional website: https://iscr.univ-rennes.fr/daniel-muller Where to apply Website https://emploi.cnrs.fr/Offres/Doctorant/UMR6226-DANMUL-005
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to commence on 1st October 2026 are now open at the School of Physical Sciences. The projects available are listed here: https://www.open.ac.uk/science/physical-science/phd-students/current-phd-studentships
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below 2 tonnes CO2e/tonne of aluminium as a supplied component and eventually to Net Zero carbon. This project is concerned with development of high strength aluminium alloys designed to provide better
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detailed information on local deformation mechanisms at the microscale, while numerical simulations and data-driven approaches will enable the development of predictive models capable of linking