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supervised by Dr Daniel Payne (Principal Investigator), Dr Calum McMullen and Dr Katja Rietdorf (Co-Investigators). The student would be required to live in the UK and within commuting distance of The Open
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Research Responsibilities Conduct original PhD research on shared and remote robotic control under uncertain communication conditions, integrating passivity-based control, machine learning, and human
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as your proposed principal supervisor, and copy the link to this scholarship website into question two of the financial details section. What happens next? Your application will be assessed by
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master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. Specialization should be in Materials Science and engineering or related subjects
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fellowship period of 3 years. The main purpose of the fellowship is research training leading to the successful completion of a PhD degree. The applicant must, in collaboration with her/his supervisor, within
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are looking for a motivated and ambitious PhD student, ideally with prior experience with additive manufacturing, solid mechanics, and architected materials. Your primary responsibilities will include: Digital
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principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion phenomena and link speciation with spectroscopic signatures. Formal requirements include a Master's degree in
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challenges in ensuring the resilience of AI in critical infrastructure. The main challenges are: a) Dynamic environments: Real-world conditions are unpredictable. Environmental factors and cyberattacks can
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. MPhil, Research Master’s degree or Master's degree in Operations Research, Econometrics or Mathematics is preferred. Candidates with an MSc or MA degree are required to successfully complete 1 year of
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contact Prof. Stéphane Bordas ( ) with CC to Dr. Jakub Lengiewicz ( ). Your profile A Master's degree in Applied Mathematics, Computational Science, Physics, Engineering, or a closely related discipline