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offered a course program tailored to your needs and the research team. The gross salary for the first year is € 2.901,- per month rising to € 3.707,- in the fourth year in according to the Collective
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Vacancies PhD Position: AI-assisted EEG Monitoring in the ICU Key takeaways Continuous EEG (cEEG) monitoring is essential for managing patients in the intensive care unit (ICU), especially after cardiac arrest or severe brain injury. Yet, clinical use is hampered by limited local expertise and...
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Institute). Qualifications We seek excellent students with a strong background in cosmology, astrophysics, physics, mathematics and/or computer sciences, who seek to obtain a Joint-PhD degree from
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Fellowship Programme (EVOLVE – EVOLVE Fellowship Programme), an initiative by six world-leading research institutes of two universities in The Netherlands (University of Groningen, Leiden University) to study
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package within the core research program of CropXR. Our goal is to develop computational methods to translate integrated simulation models of plant responses to stress (drought, heat) from a model plant
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Institute for Mathematics, Computer Science and Artificial Intelligence with the topic of responsible human-AI collaboration. The successful candidate will become a member of the Multi-Agent Systems Group
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consortium funded through the European Union’s Horizon program. Employment conditions and benefits We offer you an internationally oriented and varied job in an enthusiastic team, with excellent working
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collected in these trials will feed into the development of the Human Dietary Digital Twin—a computational model for the prediction of individual metabolic responses to complex meals. This modeling work will
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theoretical problems. Good computational/programming skills in Matlab or Python High proficiency in written and spoken English Research at our Faculty The Faculty of Science is a world-class faculty where staff
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into your PhD dissertation, supported by experienced GEM researchers; you design and apply innovative computational methods such as machine learning, to extract meaningful insights from GEM and complementary