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predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc.). Therefore, various data sources including real-time traffic counts from inductive loop detectors
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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the selection procedure. For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge
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the response period via the link below will be considered. A knowledge security check can be part of the selection procedure (for details: national knowledge security guidelines ). The interviews will be held in
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the selection procedure. For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge
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be part of the selection procedure. For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8
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be part of the selection procedure. For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8
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security check can be part of the selection procedure. (for details national knowledge security guidelines ) Only complete applications received within the response period via the link below will be
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the project. This position is embedded in the Security, Technology and e-Privacy Research Group (STeP) at the Faculty of Law and the Jantina Tammes School of Digital Society, Technology and AI research
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mathematical microbial kinetics models and quantitative risk assessments; develop user-friendly tools for quality and safety assessment of plant-based meat analogues; supervise BSc and MSc thesis research