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scope to tailor the PhD project to your interests and strengths. You will be part of a team researching the complexity and inequalities of transnational (pre-)retirement trajectories across three
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or computational science. This PhD project is part of the Gravitation programme GreenTE (Green Tissue Engineering), a multidisciplinary consortium of 7 Dutch universities. Together, GreenTE will unravel how plants
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; Participation in adapting existing and developing new model concepts regarding spray deposition and exposure to spray drift. Your team You will be part of a dynamic team, embedded in a unique organization with an
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Apply now The Faculty of Science and the Leiden Institute of Physics (LION) are looking for candidates for a: PhD in Machine Learning for Quantum Systems (1.0 FTE) Vacancy number: 15735 We
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membership and/or the outcomes of interest. This PhD studentship is funded as part of the Re-thinking Health Policy in Multimorbidity (REMIT) project. The REMIT project aims to develop new methods to assess
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(University of Reading). Dr Farhan Ahmad and Dr James Watchorn (Royal Berkshire NHS Foundation Trust). What is the project This project would suit a candidate passionate about embedding the patient voice
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. Ample opportunities to develop yourself in a scientific and/or industrial direction. Besides the opportunities offered by the research group, further doctoral training for PhD candidates is provided
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, Quantum Sensors Appl Deadline: 2025/09/31 11:59PM (posted 2024/09/24, listed until 2025/09/31) Position Description: Apply Position Description The position (post-doc, research associate, or PhD student
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research and supervision in an interactive and flexible setting? The research group of Jun.-Prof. Dr. Endo, just launched in May 2025, is looking for highly motivated candidates for PhD or postdoctoral
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
predictive and explainable digital twins. The core challenge this PhD will tackle is how to help digital twins make sense of complex, messy maintenance data and turn it into clear, useful insights