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Job Description Job Alerts Link Apply now Research Fellow in Quantum Algorithms University-Level Unit: Centre for Quantum Technologies Faculty/Department-Level Unit: Computer Science Group Employee
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of Engineering The new International Centre for Neuromorphic Systems, at The University of Manchester is hiring a Research Associate/Fellow for a two-year full-time role in Neuromorphic Systems (Algorithms). Ideal
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The new International Centre for Neuromorphic Systems, at The University of Manchester is hiring a Research Associate/Fellow for a two-year full-time role in Neuromorphic Systems (Algorithms). Ideal
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. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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at the Department of Technology Systems (ITS). The person hired in the position will work on theoretical algorithms for robust multiagent system coordination, and deploy these algorithms on a state-of-the art swarm
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differentially private learning, its connections to replicability of algorithms, and algorithmic fairness. Basic Qualifications Candidates are required to have a doctorate or terminal degree in Computer Science
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for the Research Assistant / Project Assistant posts should have an honours degree or an equivalent qualification. Applicants for the above posts should have experiences in optimisation algorithm design and
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prediction algorithm and molecular dynamics simulations. For more details, please view https://www.huilingshaogroup.com/. We are looking for a Postdoctoral Research Fellow to design and execute independent and
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in the 2025 QS World University Rankings by Subjects. We are hiring a Research Fellow in Signal Processing and Machine Learning to develop signal processing and machine learning algorithms and methods
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | about 17 hours ago
learning algorithms, as well as the adaptation and optimization of existing tools. This research aligns with CBER’s efforts to enhance the development, operations, and management of FDA’s High-performance