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partially filled containers – is a major challenge in aerospace, transport, and energy systems, where it can compromise stability and safety. The PhD will focus on developing low-order models of sloshing
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improve the efficiency, maneuverability, and noise performance of drones and other multirotor aircraft, but their deployment requires more advanced modeling and control methods. The PhD will focus
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MEng degree (or equivalent) and a PhD in Maritime Engineering and Technology or pertinent disciplines (Res Assistant if no PhD), adequate knowledge of modelling marine engines operations with alternative
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physical and numerical modelling. Feel free to reach out to the project supervisors if you have any questions. Entry requirements: The ideal applicant will be enthusiastic and self-motivated with a first
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Behaviour Demonstrable commitment to the values of equality and diversity A positive attitude and ability to act as a role model to students and colleagues Produce clear, well-structured and succinct written
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experiments, design and implement advanced detection techniques, analyse data, and carry out numerical trajectory simulations of deceleration and scattering processes. You will have the opportunity to work with
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Meritorious will be considered experience in: - Microscopy-based imaging - Immunohistochemistry - Work with clonal cell lines - Work with other model organisms such as D. melanogaster or D. rerio You are a
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. Tools for robust data and model provenance in adversarial environments. Methods for protecting training data and end users, including secure data removal and machine unlearning. Machine unlearning
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superstructures. Optimize NPL ligand shell structure in collaboration with TU Dresden to improve optical performance of NPL superstructures. Extend existing single-particle photophysical models of NPLs
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numerical methods and strategies to solve the electromagnetic and heat transfer problem in induction welding. Develop constitutive models that capture the temperature dependence of anisotropic