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Field
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, clinical trials, machine learning, optimization, or related methodological areas. Learning and applying deep learning, agentic AI, and other AI methods in assisting research is encouraged. Research
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
research on population coding and Alzheimer’s disease Key research methods: fMRI (including 7T), MEG, virtual reality (VR), a wide variety of cognitive tasks, psychophysics, machine learning, deep neural
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future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a meaningful
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. The simulations will be part of a collaboration within the EU project SHiFT in relation to the Iceland Deep Drilling Project. Your responsibilities: Conduct original research on high-enthalpy geothermal systems
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processes Implement models and perform numerical simulations Analyze and interpret simulation and experimental data Integrate AI tools and workflows to enhance modeling and accelerate learning Collaborate
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(but are not limited to) Computer Science, statistics, mathematics, automation, informatics, and Engineering. Experience in deep learning, machine learning and medical imaging processing Programming
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training of the assigned faculty supervisor. This role requires a solid foundation of discipline‑specific knowledge in plant physiology, CT imaging, and deep learning/AI, and the ability to generate
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
on LazySlide ( et al Nature Methods ), our scalable software foundation, and our deep learning framework for age prediction (Abila et al., Nature Medicine, in press) to engineer a body-scale machine learning