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Introduction Description of the research program Transplantation is the preferred treatment for patients with end-stage kidney disease. However, many transplanted kidney transplants fail prematurely. This leads
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analysis systems, to ensure safe and trustworthy results. This can involve research questions from NLP and AI like model robustness and guardrails, human-computer interaction such as interpretability and
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that would give you an advantage) Experience in computational modelling (e.g., agent-based Bayesian models, cognitive learning models, machine learning, robotics). Experience in annotation software such as
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, climate sciences, mathematics, or geo-information science or a similar relevant field, and are you proficient in programming with R/Python? Then we have the perfect opportunity for you! The Team
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Computer Science (LIACS), the Leiden Institute for Chemistry (LIC), and the Leiden Mathematical Institute (MI) at the Leiden University. Key responsibilities Conducting research on applications of (interpretable
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Organisation Job description For the National Growth Fund (NGF) project “Groeien met Groen Staal” (GGS), a PhD position for the period of 4 years is available in the context of modelling green steel
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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-proof. You will contribute to the CYCLIC project : Cyclic Structures in Programs and Proofs , a collaboration among five Dutch universities, uniting experts in cyclic structures, coinduction, program
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regarding the demand that will have to be met soon. This requires building robust models to predict future demand, making decisions under time heterogeneous uncertainty and adapting to the state
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Vacancies PhD Candidate Geospatial Risk Modelling for Climate Finance Key takeaways Effectively understanding and mitigating financial risks associated with climate change is important for