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marginal structural models will be extended with machine learning techniques for counterfactual prediction and to support sensitivity analyses Candidate The studentship is suited to a candidate with a strong
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that demand interdisciplinary solutions? Then the Program for Collaborative Doctoral Projects is the perfect opportunity for you. Many of today’s most pressing problems can only be tackled through
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, novel high-resolution imaging systems to investigate submillimeter-scale turbulent dynamics in multiphase environments such as the ocean surface. The project is part of the Collaborative Research Centre
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reinforcement learning problems. We are looking for a profile with the motivation and drive needed for making a difference that matters. You must bring an open mindset and like to create results via collaboration
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Psychopharmacology at the Faculty of Psychology and Neuroscience (FPN), supervised by Dr. Ryszard Auksztulewicz and Prof. Sonja Kotz, in close collaboration with Prof. Andre Marquand at Radboud University. You will
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groundbreaking research, providing high-quality education, offering excellent support, and fostering collaborations within and outside the university. In doing so, we contribute indispensably to a healthy, free
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and cell culture techniques are desired. The candidate is expected to work closely with an interdisciplinary research team and must be motivated to acquire new experimental skills. PROJECT DESCRIPTION
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addresses the following central research question: how can we design human-AI collaboration to mitigate biases and foster equitable decision-making? To answer this question, the research will explore areas
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HPC environments Good communication skills to interact with collaborators ranging from machine learning researchers to pathologists or medical students Knowledge of biology and medicine is a plus Highly
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sustainability goals whilst improving operational efficiency? This PhD studentship will involve developing machine learning models, creating virtual manufacturing replicas, and implementing optimisation algorithms