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Funded PhD Studentship in applied geospatial ecology. This project will investigate how dryland vegetation productivity varies across space and time and how it responds to land management. Working with NEOM, one of the world’s largest ecological restoration programmes, the project will develop...
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integrating machine learning, computational modelling, and experimental validation. The successful candidate will receive training in both computational and experimental biology within a highly collaborative
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also be involved in a fixed number of teaching hours during your time with us. In year one, alongside your specific PhD research modules, you’ll complete a short teacher training programme by
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, including the Teacher Education Programmes, the Sport Science Programme, the Human Resource Management Programme, the Behavioural Science Programme with a focus on IT environments, and the Police Education
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One start-up scholarship (for 1 year) within the Department of Ancient Civilizations at the University of Basel The PhD program of the Department of Ancient Civilizations at the University of Basel
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interactions and nanophotonics, as well as to theoretical physicists in the Department of Mathematics and Computer Science. We collaborate closely with scientists of the ALPS II collaboration and parts
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opportunity to join the Emerging Technology and Materials research group within the School of Mathematics, Statistics and Physics. You will carry out research as part of a team of researchers working
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I supervise projects considering the evolution of accretion discs and their connection to observations. In particular, I consider discs that are warped or distorted (not flat). This geometry has been directly observed in planet forming discs around young stars (protoplanetary discs) and is...
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(CeRA) specializes in research on male reproductive function. In a multidisciplinary project funded by the Federal Ministry of Research, Technology and Space (BMFTR), we want to research novel approaches
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The rapid growth of deep learning has come at an extraordinary environmental and computational cost, yet the standard training paradigm remains remarkably unchanged. Every sample is passed through