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exciting opportunities for machine learning to address outstanding biological questions. The PhD student to be recruited will be working on the development of machine learning methods for single-cell data
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dynamics simulations is highly desirable. Basic knowledge of machine learning is considered an advantage but is not mandatory. LanguagesENGLISHLevelExcellent Additional Information Work Location(s) Number
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for
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application! We are looking for a PhD student in biomedical engineering with a focus on deep learning for medical images Your work assignments The position focuses on developing methods for federated learning
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Superior Técnico, Portugal and 27 associated partners (from 10 countries) Format: double PhD degree, granted by two universities in Europe; see the list of main partners: https://www.eu4greenfielddata.eu
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on the intersection of robotics and control theory. Project description: This PhD project aims to develop learning‑based methods that combine expert demonstrations with experiential reinforcement learning to enable
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; Distributed multi-agent sensing and cooperative positioning algorithms; Machine learning and data-driven methods for ambient awareness. Working Environment: The PhD will be conducted at the University
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Research Framework Programme? Horizon Europe - ERC Is the Job related to staff position within a Research Infrastructure? No Offer Description The Machine Learning for Integrative Genomics team (https
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data set (e.g. neutron irradiations, that take years/decades to generate). Digilab brings AI/ML (artificial intelligence / machine learning) approaches for data engineering and automation to utilise
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background in the topics related to this PhD position. Good knowledge of combinatorial optimization (scheduling problems, mathematical modelling etc.), machine learning and/or strong programming skills