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Field
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approaches to optimize the trade-off between privacy and utility especially in the context of large models. Advance knowledge of key AI methods such as deep learning, algorithm design, probability theory
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supervision of Master’s students and PhD researchers. Take part in open science and code sharing. Skills, expertise and qualifications A PhD degree in computational biology, machine learning, computer science
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strong technical expertise in deep learning, such as models for image segmentation, classification, multi-modal processing, foundation models, or agentic frameworks. An extensive background in computer
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Class Acad Prof and Admin Add to My Favorite Jobs Email this Job About the Job Research Description The project aims at combining three primary data sets (JWST NEXUS spectroscopy, Euclid Deep Field North
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results-oriented team player. Ideal profile includes following competencies and experience: Strong programming skills, deep statistical knowledge and a proven track record with machine learning Solid
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scattering and direct dark matter detection, using advanced cryogenic detectors. The MBI hosts a research group dedicated to Machine Learning in Particle Physics. Qualifications: PhD in Particle Physics
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their valuable contributions and deep connection to country and pay respect to Elders past and present. Advance internationally recognised Antarctic climate and palaeoclimate research Be part of nationally funded
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Learning (ML), Deep Learning (DL) particularly in Natural Language Processing (NLP) and Computer Vision (CV) - strong record of publications - Excellent communication skills and ability to work in a fast
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, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector CT with work in
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learning to understand and predict the behavior of cardiovascular tissues and organs across scales. You will work closely with PhD students, MSc students, and international VITAL partners. This is a full