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and societal partners in migration and urban studies. A comprehensive training programme combining theoretical courses, advanced methods, and transferable skills. Joint supervision by leading academic
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treatment strategies adapt to accommodate evolving patient preferences as the advanced prostate cancer disease progresses? The doctoral training programme offers: Core training in health economics, causal
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economics aims to give dedicated graduates a solid training in performing high quality scientific research in economics, making use of state of the art empirical and theoretical techniques. The programme
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such networks and to unleash further features, in particular positioning, tracking mobile devices, and sensing. By addressing these research questions you contribute to making OWC technology mature for use in
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qualifications You have graduated at Master’s level in Electrical Engineering, Computer Science, or Applied Mathematics or completed courses with a minimum of 240 credits, at least 60 of which must be in advanced
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Acceptable first degree - Physics, Mathematics, Natural Sciences, Engineering, Computer Sciences. The standard minimum entry requirement is 2:1. Mode of study: Full-time Start date: 1st October 2026 Funding
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Information science Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Country Norway Application Deadline 25 Jan 2026 - 23:59 (Europe/Oslo) Type of Contract Temporary Job Status
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. The doctoral training programme offers: Core training in health economics, causal inference, micro-econometrics, health inequalities, epidemiology, and healthcare decision-making. Elective courses on data
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Description Where: At the Chair for Computational and Theoretical Biology ( CCTB ) and the Center for Artificial Intelligence and Data Science ( CAIDAS ) of the University of Würzburg. Project
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Application deadline: 07/01/2026 Research theme: Theoretical Physics, Quantum Theory, Quantum Information, Applied Mathematics How to apply: https://uom.link/pgr-apply-2425 UK only This 3.5 yearlong