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Field
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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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grow. We welcome you to join our community of faculty, students and alumni who are shaping the future of AI, Data Science and Computing. Key Responsibilities: Designing and developing scalable algorithms
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/Anders Lien 9th September 2026 Languages English English English PhD Research Fellow in Machine Learning for Cognitive Neuroscience Apply for this job See advertisement About the position Position as PhD
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Fellow to conduct cutting-edge research in high-resolution electromagnetic imaging and intelligent sensing. The successful candidate will contribute to the theoretical development, algorithm design, and
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by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain
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on Multimodal Intelligence. The role involves developing and advancing novel algorithms for emerging challenges in Multimodal Intelligence, including Multimodal understanding and generation. The candidate is also
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, converter control, and energy systems. Design, model, simulate, and develop advanced power electronic converter topologies and associated control algorithms. Investigate high-efficiency and high-power-density
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fundamental physics and quantum computation, with an emphasis on building quantitative, benchmarked pipelines that connect field-theoretic questions to modern quantum algorithms and hardware. The position will
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fusion of sensor data and energy harvesting output, enabling adaptive and energy-aware data acquisition from textile-based wearable systems. Build adaptive algorithms that dynamically optimise data
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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