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data from a recently completed clinical trial (https://www.nejm.org/doi/full/10.1056/NEJMoa2408114 ), you will build and evaluate multimodal machine learning models that integrate these data to predict
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| Collective bargaining agreement: §48 VwGr. B1 lit. b (postdoc) Limited until: 31.03.2032 Reference no.: 5115 Explore and teach at the University of Vienna, where over 7,500 brilliant minds have found a unique
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Postdoctoral Researcher in ML for Dynamical Systems Representation, Prediction, and State-estimation
from all backgrounds to join our community. The Nonlinear Systems and Control group is seeking a talented and ambitious Postdoctoral Researcher to develop machine learning-enabled approaches
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an Athena Swan Bronze award, highlighting its commitment to promoting women in Science, Engineering and Technology Machine Learning, AI Safety, AI Alignment, Eval of LLMs, Multi-agent Safety
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Aalto University is inviting applications for a Postdoctoral researcher in molecular machine learning. The successful applicant will join the research group of Professor Juho Rousu. The position
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the Department of Physics. Machine learning has made enormous progress during recent years, entering almost all spheres of technology, economy and our everyday life. Machines perform comparably to, or even surpass
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for continuous tremor monitoring in Parkinson’s disease. Working with Dr Anne Bernassau and Prof Marc Desmulliez, the PDRA will support hardware optimisation, data acquisition, machine-learning
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possible for up to 1 day/week. You will join an interdisciplinary team of researchers spanning imaging science, machine learning, genetics, and population health, working closely with collaborators
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical