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Academic Job Category Faculty Non Bargaining Job Title Postdoctoral Research Fellow, Machine Learning Department Cooper Laboratory | Department of Orthopaedics | Faculty of Medicine (Anthony Cooper
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experimental disease models to identify disease mechanisms, discover therapeutic targets, and improve disease prediction, prevention, and treatment. Our research focuses primarily on substance use disorders and
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by ARPES, pursue scalable wafer-scale moiré epitaxy, develop epitaxial superconductors for quantum computing and integrate machine learning for automated high-throughput MBE. We are particularly
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record in machine learning, with preference for expertise in representation learning, deep embeddings, contrastive learning, or foundation models. Solid background in linear algebra, probability, and
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analyzing hyperspectral data and developing machine learning models - Genetic or molecular lab experience - Bioinformatics, or statistical genetics experience - Excellent written and oral communication skills
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teams. Job scope: • Research o Develop research questions, study designs, and analysis plans using SPHS data. o Conduct statistical analyses, longitudinal modelling, or machine learning approaches as
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with the Ganna Lab (https://www.dsgelab.org/ ) at FIMM and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami
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Department of Computer Science of Faculty of Science invites applications for a DOCTORAL RESEARCHER IN MACHINE-LEARNING, STATISTICS AND DATA-CENTRIC ENGINEERING starting from September 2026, or as
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insurance, supported by INESC TEC. 2. OBJECTIVES: • Research novel deep learning models for anatomically structured EGGIM estimation.; • Develop methods for image-level and examination-level reliability
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and the Probabilistic Machine Learning Lab (https://www.helsinki.fi/en/researchgroups/probabilistic-machine-learning ; groups of Acerbi and Klami) at the Department of Computer Science, aligning with