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university degree (diploma, master's degree) in transport or traffic flow or related study programs. Solid knowledge of at least one programming language, preferably Python, experience in model-based
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immune cells in cell culture and murine models of inflammation and cancer Collecting, analyzing and annotating MRI data Combining MRI and mass spectrometric imaging data in data base for quantitative MRI
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talented PhD Candidate for the Division of Personalized Immunotherapies Reference number: 2025-0252 The Division of Personalized Immunotherapy (headed by Prof. Dr. Özlem Türeci) at HI-TRON Mainz is looking
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Wetsus - European centre of excellence for sustainable water technology | Netherlands | about 1 month ago
operational performance. Based on feedwater composition (salinity, monovalent/divalent ion ratios, and valuable elements), you will model and design ED configurations that produce tailored concentrate streams
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of the PhD topic (subproject A7- Reinforcement learning for mode choice decisions): This PhD project will develop and implement a Deep Reinforcement Learning (DRL) model for dynamic mode choice within
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. This exciting project is funded by a Industry PhD Program. Flinders University and Bookbot.com, are partners in the program. The student will be based at Flinders University for 4 days a week. The candidate will
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from the Newcastle Urban Observatory, public transport ridership data, questionnaires and travel surveys, and the DARe MATSim agent-based modelling suite, this PhD will seek to gain a deeper
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/ Robust) Combinatorial Optimization, Game Theory, and Network Theory, as well as Artificial Intelligence. Potentially, scenarios could be simulated using agent-based, discrete-event, or other techniques
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the Netherlands and who has made an outstanding contribution to the humanities or social sciences. The researcher must have obtained their PhD no more than 15 years prior to the year of their nomination and have an
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infinite extent models and limited extend data based on trust over particular sets, and naturally create explainable AI structures which can further be analysed from a verification and validation perspective