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are seeking a motivated, enthusiastic, and curious PhD candidate to join our Health Technology and Services Research (HTSR) section at the Faculty of Behavioural Management and Social Sciences. At HTSR, you'll
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Machine Learning Problems > Constantly questions finance/trading data and stays motivated to seek answers despite most often proving that there is no correlation or signal > Experience in setup of research
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directed evolution of biocatalysts predictable by machine learning. As part of the ML-GUIDE team, you will closely collaborate with researchers to identify commonalities and distinct aspects of engineering
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(+/–) applied to the electrodes can be optimised in a machine-learning approach to optimise the gel morphology and the embedded stimuli-transduction pathways towards the targeted mechanical behaviour. Departing
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, business school scientists, system modeling and optimization researchers, computer scientists, legal experts and social scientists working on energy topics. Description of the PhD project The project
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and a scientific programmer. You will be supervised by both Rianne de Heide and Jelle Goeman. One PhD student will be appointed at the UT, and one PhD student at the LUMC. We collaborate very closely
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that can be used for training machine learning and deep learning models. You will work in tight collaboration with other researchers in Nijmegen, Delft and at the Hubrecht Institute (van Oudenaarden group