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Postdoc in Generative Machine Learning for Biomedical Data | Human Technopole, Milan Build the science that shapes the future of human health. Application closing date: 21.02.2026 Join a place where
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microscopy data analysis, chemometrics, and machine learning. This position is ideal for a researcher who enjoys working at the interface of imaging, data science, and environmental monitoring. The project
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. Experience in high-throughput sequencing data analysis and cluster/cloud computing. Proficiency in variant calling, single-cell DNA and/or RNA analysis, and machine/deep learning (preferred but not required
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applications, for example in machine learning and mathematical statistics Participation in the scientific activities of the department, e.g. seminars, workshops and schools organised by the members
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of competitive research proposals. You should have experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction
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technologies (fiber-optic sensors, DIC), and computer science (machine learning tools) in collaboration with de department of Physics. The aim of the BriCE project is to develop a novel bridge monitoring
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, and machine learning. The environment at GBI will allow researchers to undertake ambitious, long-term, collaborative research, and we will actively support the translation of research to commercial
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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Engineering or a related field The ideal candidate should have some knowledge and experience in the following topics: Software Cybersecurity Software Testing and Analysis Machine Learning and Multimodal Large
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), proteomics (LC-MS/MS), (epi)genomic data processing, multi-omics integration, machine learning approaches for high-dimensional data, confocal / two-photon imaging, tissue clearing and light-sheet microscopy