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Post-doctoral Researcher in Multimodal Foundation Models for Brain Cancer & Neuro-degenerative Disea
Qualifications PhD in machine learning, computer vision or a related field. Established expertise in deep learning methods applied to images analysis. Experiences with generative models, volumetric image
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developing new machine learning methodologies that tackle unique computational problems in healthcare applications. We use large real-world complex datasets, including data extracted from electronic health
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Vision Profiler (UVP), and to analyse its spatial and temporal variability. This will be done by combining different data sources and machine learning (ML). Data used for this ML approach include - a
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(or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs. The candidate will apply
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About the Position We are recruiting a Postdoctoral Research Associate to join Tom Hartvigsen’s research group in UVA’s School of Data Science. The postdoc will work on developing machine learning
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, biomedicine, and other areas of societal importance. Coding and/or machine learning experiences are highly valued. Specific projects may involve developing multiscale simulation methods for quantum mechanical
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27.10.2025 Application deadline: 30.11.2025 Are you excited about the possibility to explore ethical, philosophical, legal, epistemic or social implications of using machine learning in different
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, evolutionary biology, computer science, physics, applied mathematics, or engineering. Our research integrates mathematical modeling, machine learning, and quantitative experiments to understand and control
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: This project is related to machine learning for Urban Informatics. In this context, the intersection between the urban infrastructure and digital technologies plays an essential role. The aim is to develop
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State University and work closely with I-CREWS researchers across the state. The position emphasizes developing, integrating, and applying modeling approaches-including machine learning (ML), hydrologic