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Field
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of tax data. Core goals include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools
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of tax data. Core goals include creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools
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BMS constraints. Experience with system identification, uncertainty-aware modelling, large datasets, and machine learning. Evidence of research capability through a thesis, publications, conference
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Join the Responsible Machine Learning (ML) Group at the Faculty of Computer Science. Led by Prof. Dr. Martin Pawelczyk, who recently joined the University of Vienna from Harvard University, our research
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for latent variables and their connections to modern machine learning. The project combines methodological research in statistics with applications to large-scale social science data. The successful candidates
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UiO/Anders Lien 4th October 2026 Languages English English English 3-years PhD position in probabilistic machine learning and statistics Apply for this job See advertisement About the position We
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5 Sep 2026 Job Information Organisation/Company Radboud University Medical Center (Radboudumc) Research Field Engineering » Biomedical engineering Engineering » Computer engineering Researcher
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machine learning-driven digital twins for predictive combustion modeling. The research program will cover a wide range of e-fuels (H₂, NH₃, CH₃OH, DME, OME) and their applications in industrial furnaces
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machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a biological reference point for identifying disease-specific biomarkers. A central part of the
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials