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sustainability. The research will delve into power-aware computing strategies, thermal management, and the development of algorithms that balance performance with energy consumption. Students will aim to create
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, Department of Computer Science, the Technical Faculty of IT & Design and the Center for Clinical Data Science (CLINDA) and Center for General Practice (CAM), Department of Clinical Medicine, the Faculty
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to improve our understanding of disease and the effectiveness of treatments, and implementing AI algorithms to deliver safer and more efficient care. The student will have access to a unique training programme
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11 Mar 2026 Job Information Organisation/Company cellumation GmbH Department HR Research Field Engineering » Computer engineering Engineering » Mechanical engineering Researcher Profile First Stage
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real-time? This project will use computational models of neural networks to derive closed-loop control algorithms to modulate oscillatory dynamics in brain circuits. You will test these algorithms
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) Established Researcher (R3) Application Deadline 9 Apr 2026 - 00:00 (UTC) Country Hong Kong Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded
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(Berlin) in a close partnership with the Forschungszentrum Jülich, contributing to algorithm development, computational tool implementation, and validation with experimental partners (TU Graz and
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on developing the simulation models, data models and algorithms required to enable connected cross-disciplinary design and optimisation, laying the foundations for more integrated and intelligent engineering
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We are seeking a highly motivated PhD student to perform fundamental research and to conceive truly sparse solutions (on both, CPU and GPU) for dynamic sparse training, aiming to cut the training costs and energy requirements of state-of-the-art deep learning models significantly, while...
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precision medicine based on gene sequencing time series data. Large data sets come with significant computational challenges. Tremendous algorithmic progress has been made in machine learning and related