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in biomedical informatics is available at Harvard Medical School to work at the intersection of advanced machine learning and large-scale biomedical data. The selected fellow will join a dynamic
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with strong foundations in modern machine learning and the ambition to advance foundation models, agentic systems, and new AI approaches for high-impact scientific applications. We seek candidates with
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real-world problems. Ideal candidates will have demonstrably strong research skills, evidenced by multiple publications in top-tier machine learning or artificial intelligence conferences and/or leading
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brain disorders such autism spectrum disorder and bipolar disorder, by utilizing recent advances in genetics and genomics, and through collaborations with groups using machine learning. We are
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4 years is possible. About the team 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
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and artificial intelligence/machine learning may be applied are encouraged to apply. If you are interested in research in brain-machine interfaces, and are unsure about whether you have the right
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foundations in modern machine learning and the ambition to build brain foundation models and other AI systems that advance our understanding of neural activity, brain circuits, and biologically grounded
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Job Description Are you passionate about using atomistic simulations and machine learning to accelerate the green transition? Do you want to understand, atom by atom, why electrolysers degrade, and
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establish a physical laboratory research program at both institutes. We seek to recruit a computational researcher with expertise in machine learning and mathematical modelling whose work addresses
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establish a physical laboratory research program at both institutes. We seek to recruit a computational researcher with expertise in machine learning and mathematical modelling whose work addresses