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machine learning, mathematical modelling and algorithm design to enable autonomous operation of large satellite constellations. You will also develop an open-source simulation and benchmarking platform
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(required) Knowledge of quantum computing or quantum algorithms (advantageous but not essential) Strong analytical skills, curiosity for interdisciplinary research, and the ability to collaborate effectively
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or quantum algorithms (advantageous but not essential) Strong analytical skills, curiosity for interdisciplinary research, and the ability to collaborate effectively with both academic and industry teams
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learning, and software programming Proficiency in Python and machine learning frameworks such as PyTorch (required) Knowledge of quantum computing or quantum algorithms (advantageous but not essential
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an opportunity for a Research Associate to develop quantum-enabled synchronisation algorithms for deployment on space-based platforms. You will contribute to research involving quantum and classical optical
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The successful PhD candidate will undertake research in the following areas: Develop deep learning algorithms for autonomous robotic navigation using dual-view image fusion and shadow-based visual perception
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machine learning can be used to understand complex behaviours such as reliability, competence, transparency and trust. The position will design and develop innovative reasoning algorithms and knowledge
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validate wearable data algorithms, software tools and pipelines supporting large-scale, multi-cohort research. It will contribute to the ProPASS federated data analysis platform, including testing
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complexity theory, quantum algorithms, optimisation and quantum sensing. Your work will contribute to the development of new computational frameworks and approaches spanning sensing optimisation, adaptive
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estimation, confidence calibration, model routing, token selection, early exiting, adaptive visual processing, and efficient use of multiple foundation models. The work will combine algorithm development with