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embedded within the Quantitative Healthcare Analysis (qurAI) group and conducted in close collaboration with the CARA Lab and clinical partners in the Netherlands and abroad. You will work with large, multi
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group members; discuss work with group members and at departmental meetings, and incorporate feedback; take a leading role in writing manuscripts for publication in peer-reviewed journals and conferences
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, targets the conversion of intermittent electricity to platform chemicals and fuels making use of dynamically operated processes. This is a promising route to alleviate net congestion and make more effective
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, including physics-informed neural networks, neural operators, hybrid physics-ML approaches, and emerging foundation-model paradigms for scientific data. Scientific machine learning is increasingly important
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these insights into concrete, evaluated tools for HTA assessors. Your job You will be on the frontline of using and implementing GenAI in the cyclic HTA approach to medicines. Possible work topics include: Mapping
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materials and experimental tasks, analyse behavioural data, apply computational modelling techniques, and write scientific articles that will form the basis of your dissertation. You will work closely with
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functioning, and whether these effects can be strengthened by adding multisensory immersive Virtual Reality. You will work with older adults and patient groups, including individuals with mild cognitive
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months, contingent on a positive performance evaluation within the first 12 months. The preferred starting date is 01 February 2027; Based on a full-time appointment (38 hours per week) the gross monthly
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tasks, analyse behavioural data, apply computational modelling techniques, and write scientific articles that will form the basis of your dissertation. You will work closely with your supervisors, another
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What you will be contributing As a PhD candidate you will contribute to improving our understanding of the interplay between phytoplankton traits and lake ecosystem functioning. Specifically, you