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Research Framework Programme? Horizon 2020 Is the Job related to staff position within a Research Infrastructure? No Offer Description Machine learning for gravitational waves, LISA data analysis Where
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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fields. Your research can be theoretical, applied, or span both. Deadline February 9, 2026. Where to apply Website https://jobrxiv.org/job/ellis-institute-finland-27778-postdocs-in-machine-learn
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. The PhD will combine behavioural experiments, machine learning, and explainable-AI methods to answer questions: Do SR techniques improve human face identification accuracy? How do SR-enhanced images affect
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team (https://research.pasteur.fr/en/team/machine-learning-for-integrative - genomics/) at Institut Pasteur, led by Laura Cantini, works at the interface of machine learning and biology (tools developed
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Vision Center (CVC, https://www.cvc.uab.cat ) is a center with over 150 persons, working on machine learning and computer vision research for more than 30 years, placed at the Universitat Autònoma de
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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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of sea turtles - Developing innovative machine learning methods to analyze the sounds associated with these behaviors - Automating the processing of audio and visual data to optimize the quantity and
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Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
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George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Târgu Mureș | Romania | 7 days ago
Methods and Programs in Biomedicine Update, 2024, 5:100148. https://doi.org/10.1016/j.cmpbup.2024.100148 de Hond, A.A.H., Leeuwenberg, A.M., Hooft, L. et al. Guidelines and quality criteria for artificial