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at the Plant Physiology department. In a Sectorplan-funded collaboration between six departments around the Theme ‘Evolution as a process of interactions between scales’, we focus on ‘Predicting
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the research group of Dr Danny Incarnato, at the Groningen Biomolecular Sciences and Biotechnology Institute (GBB) of the University of Groningen (The Netherlands), to investigate RNA structural ensemble
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position within a Research Infrastructure? No Offer Description Spurred by the advancements in Artificial Intelligence (AI), a wave of prediction models is reaching healthcare, with some already employed in
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departments of the Plant Science Group around the Theme ‘Evolution as a process of interactions between scales’, we focus on ‘Predicting transitions’ and will hire three postdocs to work on different aspects
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Sciences and Biotechnology Institute (GBB) of the University of Groningen (The Netherlands), to investigate RNA structural ensemble dynamics in living cells. What The successful applicant will work on a
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machine learning to provide insights into the decisions of complicated machine learning models. For instance, why does a machine learning model predict that it is unsafe to discharge a certain patient from
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other data analytics models to the study of armed conflict, political violence, and (counter-)terrorism, and conduct independent and collaborative research. The ultimate goal is to improve predictive
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process of interactions between scales’, we focus on ‘Predicting transitions’ and will hire three postdocs to work on different aspects of evolutionarily interesting transitions (see also other vacancies
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and material performance remains unclear, let alone inverse design of these molecules. The goal of this project is to develop ML models for: 1) predicting properties of oligopeptide materials based
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order and chaos and, thereby, different time scales of predictability. Famous examples include various states in the transition to turbulent fluid flow or metastable chemical configurations. However, such