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related to staff position within a Research Infrastructure? No Offer Description The Department of Computer Science in the Faculty of Science is looking for a full-time (100%) Machine Learning Engineer
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application of cutting-edge causal machine learning methods You will further elaborate and concretise the PhD theme and research tasks at the start of the PhD in consultation with the supervisor and any co
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, contains: You mainly conduct research with to obtain a PhD. Subject: Enhancing decision-making through the development and application of cutting-edge causal machine learning methods You will further
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), consists of two main parts. First, the candidate will develop machine learning models aimed at improving the follow-up of neurocognitive function in critically ill children after discharge from the intensive
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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2023 as the 10th VIB center, with the core mission to study fundamental problems in biology by combining machine learning with in-depth knowledge of biological processes. We aim to work towards
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currently exploring a range of exciting topics at the intersection between computational neuroscience and probabilistic machine learning, in particular, to derive mechanistic insights from neural data. We
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and Delivery: Design and develop training programs on Data Science and AI topics, including machine learning algorithms, data visualization, and statistical analysis. Provide foundational sessions about
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
Integration of phenotypic data with omics analysis Explore machine learning and network analysis methods Profile Essential A PhD in Bioinformatics, Computational Biology, Evolutionary Biology
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and building and maintaining machines and automation, preferentially with experience in plant biology. Job description Maintenance of automated phenotyping systems, containing conveyer belts or gripper