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15 Aug 2026 Job Information Organisation/Company Leiden University Research Field Biological sciences » Biodiversity Computer science » Programming Researcher Profile Recognised Researcher (R2
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curious to deliver work that matters, your journey starts here! The Civil and Environmental Engineering Department at Carnegie Mellon offers a unique interdisciplinary program that enables you to develop
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, the Postdoctoral Researcher will drive research at the intersection of health data science, multimodal AI, digital twins, computational phenotyping, and responsible AI. PhD must have been received within the last
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Fellowship Description Applications are invited for Fields Postdoctoral Fellowship positions with the Thematic Program on Quantum Algorithms for Differential Equations (the "Program") taking place
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-grade algorithms. Demonstrated ability to work on complex data analysis problems and deliver robust computational solutions. Excellent communication skills and a strong interest in interdisciplinary
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
Health, powered by the All of Us Research Program is a new initiative to develop algorithms that predict individual responses to food and dietary patterns. The NPH Consortium consists of 12 awardees across
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Deadline 23 Jul 2026 - 22:00 (UTC) Country Germany Type of Contract To be defined Job Status Other Offer Starting Date 2 Jul 2026 Is the job funded through the EU Research Framework Programme? Not funded by
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 3 months ago
strategies, signal processing algorithms and simulation platforms for goal-oriented semantic wireless systems. Drive a high-impact ARC Discovery Project aimed at advancing sovereign telecommunications
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& Machine Learning: Advise program managers on the state-of-the-art application of data science and AI/ML, evaluating the technical merit of proposed algorithms and models to guide investment in next
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quantum chemical methods and machine learning; developing quantum algorithms for computational chemistry on quantum computers; and applying existing and new computational methods to study multiscale