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learning algorithms to support research in IDMxS. Key Responsibilites: Apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS. Help supervise
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Job Description Job Alerts Link Apply now Research Assistant in Quantum Algorithms and Machine Learning University-Level Unit: Centre for Quantum Technologies Faculty/Department-Level Unit
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to develop an online framework for assessing fatigue, structural integrity, and operability of multiple floating offshore wind turbines, supported by computationally efficient learning algorithms with
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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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contributing to the design and development of advanced models, algorithms, and AI‑driven systems for renewable energy microgrids and data centers. The Research Assistant will work closely with laboratory
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or an equivalent qualification; (b) be familiar with deep learning algorithms and agent development; and (c) motivation to pursue accomplishments. Applicants are invited to contact Dr Zhou Yanghong
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. The position will focus on developing computational algorithms and tools for the analysis of mass spectrometry-based proteomics data. Research projects will center on advancing the FragPipe computational
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optimisation, algorithm design and high-performance computing, with application to airport innovation. Successful candidates will join an active group of Principal Investigators and researchers to work within
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guidance, navigation, and control (GNC) systems. The successful candidate will develop and validate Bayesian and non-Gaussian estimation algorithms, data assimilation methods, and tracking frameworks
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) to develop accelerated AI, machine learning, and robotics algorithms with a strong focus on computational efficiency, memory reduction, and energy-aware deployment. The role targets foundation models