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London) has multiple, fully-funded PhD studentships available to accelerate its interdisciplinary research in the humanities, social sciences and digital sciences. Each scholarship is fully-funded
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Salary Funding covers tuition fees (approx £5-8k per year) and a tax free living allowance for 3 years (approx £22-£24k per year if studying full time). A funded PhD position is available to work
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equations (PDEs). The position is funded by the Dutch Research Council (NWO) via the Vidi research project Optimal adaptive space-time boundary and finite element methods. The project focuses on the design
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includes an extension of up to 6 months if approved for your candidature. This is the full-time, tax-exempt rate which will index annually. You will receive a tuition fee offset/sponsorship, covering
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and enhance N storage in artificial aquatic ecosystems. This project is structured around four themes, and as such there will be multiple avenues for contributions that can be collaboratively designed
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application! Data-driven life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular
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available through i‑Risk and Newcastle University. A willingness to engage with quantitative and computational approaches is the key requirement. Some familiarity with geospatial data or basic programming
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22 Apr 2026 Job Information Organisation/Company CNRS Department Centre de Recherche sur la Biodiversité et l'Environnement Research Field Biological sciences Environmental science Researcher
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Max Planck Institute for the Study of Crime, Security and Law | Freiburg Elbe, Niedersachsen | Germany | 4 days ago
20 Apr 2026 Job Information Organisation/Company Max Planck Institute for the Study of Crime, Security and Law Department Criminology Research Field Criminology Psychological sciences » Psychology
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overcoming significant technical hurdles: a) Adaptive Fault Monitoring: Traditional systems fail to identify root causes in multi-modal data streams; this project utilizes federated learning and graph neural