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Department of Mathematics at Radboud University is seeking an outstanding, highly motivated PhD candidate in Mathematics of Nonlinear Acoustics. As a PhD candidate, you will develop novel mathematical methods
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PhD position - Modelling the emergence of information transfer in prebiotic self-replicating systems
the PRELIFE program we offer 15 exciting research projects which can be found at www.prelife.originscenter.nl of which the research project of the current PhD position is one. This project aims at uncovering
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Apply now The Faculty of Science and the Leiden Institute of Advanced Computer Science (LIACS) are looking for: PhD Candidate, Reinforcement Learning for Sustainable Energy This position is embedded
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PhD Position: Activating Heritage as a Mediator for Dialogue and Belonging in an Era of Polarization
This PhD project examines how heritage can be activated to support dialogue and strengthen connections between migrants and local communities. It addresses key societal questions about how people
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Vacancies PhD opening: Intra-wave modeling of coastal nourishment morphodynamics Key takeaways This research position is part of the NWO-funded SOURCE program: Sand nOURisment strategies
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. At www.bprc.nl you can read which subjects have our special attention and how we conduct our research. We are looking for a PhD student (4 years) The project: You will be joining the Department Neurobiology
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PhD position on Microbial Genome Evolution Faculty: Faculty of Science Department: Department of Biology Hours per week: 36 to 40 Application deadline: 29 May 2025 Apply now Join us to explore
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matter and smart materials? Then come and join our team as a PhD candidate! Materials that spontaneously ’morph their structure and optimise themselves to particular functions will open entirely new
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This PhD position offers a unique opportunity to explore an innovative and socially relevant research topic at the intersection of migration, fatherhood, masculinity, emotions, and family-making. You
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Vacancies PhD position on Dependability Driven on Device Learning Algorithms for Embedded Neuromorphic Architectures Key takeaways Edge devices that can learn autonomously while guaranteeing