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The Department of Built Environment https://www.oslomet.no/en/about/tkd/be at Oslo Metropolitan University has a vacancy for a PhD candidate available in the area of railway systems/railway sleepers in UHPC
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literature. Main responsibilities • Design, implement and optimize signal-processing, statistical and machine-learning algorithms for eye-movement (oculomotor) and voice/speech data. • Validate
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optimization. Strong programming skills (Python, Julia, Jax). Experience with numerical optimization is also desirable. Personal characteristics To complete a doctoral degree (PhD), it is important that you are
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of recruitment. Must fulfil the conditions for enrolment to PhD programme at the host institution. For details about the criteria, please refer to detailed description of positions found at https://desire-msca.eu
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further doctoral training for PhD candidates in the framework of the KU Leuven Arenberg Doctoral School ( https://set.kuleuven.be/phd ), known for its strong focus on both future scientists and
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candidate will contribute to cutting-edge research in optimal control theory, differential game theory, mean-field game theory, and mean-field-type game theory, developing advanced mathematical frameworks and
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, noting ORIE's long term interest in building strength in discrete optimization. Requisite is a strong interest in the broad mission of the School, exceptional potential for leadership in research and
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2026 (or as agreed). Description of PhD Project The PhD student will be responsible for leading projects focused on the development of novel computational and AI tools to improve our understanding
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its global impact. Candidates should hold a PhD in Mathematics or a closely related field and possess the stature of a full Professor at a research-intensive institution. The most highly qualified
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 8 hours ago
across the counselling team. Lead continuous renewal, and optimization of the counselling service delivery model, ensuring services remain responsive to evolving student needs, emerging best practices, and