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learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will have the chance to explore basic machine learning research as
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are looking for candidates interested in developing new machine learning methods for medical image analysis, with a particular focus in anomaly detection and unsupervised learning. In this position, you will
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implement a hyperspectral imaging system tailored to bulk forensic trace analysis and develop chemometric and machine-learning models for material identification and classification. You will evaluate
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advanced analytical approaches, including deep learning and machine learning, to improve disease subtyping and risk prediction. You should have a strong willingness to learn, enjoy tackling challenging
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industrial energy systems that combine physics and data to become adaptive, autonomous and trustworthy? To get there, you will work at the intersection of thermal energy systems, machine learning and
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, cryo-electron microscopy (cryo-EM), cryo-EM-based polyclonal serology (cryo-EMPEM), molecular dynamics simulations, machine learning, and structural biology to define epitopes and engineer improved
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, and machine-learned force fields to describe ion transport and interfacial evolution. These models will be extended to mesoscopic and continuum scales (kinetic Monte Carlo, phase-field) to capture
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and computer scientists to confront sexism in GenAI technologies with the Associated Partners. About the Department of English, Germanic and Romance Studies The Department of English, Germanic and