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and evaluation. The post holder will take a leading role in advancing theoretical and algorithmic research in the domain of probabilistic preference aggregation, contribute to the design and analysis
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, including: Robot Learning: Creating algorithms that empower robots to learn autonomously from interactions and adjust to new tasks. Manipulation: Enhancing techniques for precise and adaptable object handling
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help supervise associated PhD students. The successful candidates will join large, supportive research teams led by Profs Knight, Screen and Connelly all working collaboratively at Queen Mary. This is an
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to numerical simulation algorithms? Then apply now to join our team of theoretical researchers in the Quantum Information and Quantum Many-Body Physics research group. Your personal sphere of play: As a
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We are seeking a full-time Postdoctoral Research Assistant in “Resilient Temperature- and Pressure-Sensitive Paints for Hyperspectral Imaging” to join Prof. Jin-Chong Tan’s group (Multifunctional
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Formstone (see Panousopoulou et al. J. Cell Sci. 2016 (https://doi.org/10.1242/jcs.180703) and Prof. Philippa Francis-West (Mao et al. Nature Comms. 2016 (https://doi: 10.1038/ncomms11469 and Prof. Philippa
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. The successful candidate will work at the intersection of multi-disciplinary modelling, advanced AI algorithms, and decision-support tool development. Responsibilities will include programming, analysing and
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algorithmic graph theory. The purpose of the role is to contribute to the project "Algorithmic meta-classifications for graph containment", working with Professor Matthew Johnson, Dr Barnaby Martin and
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the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
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of original machine-learning based algorithms and models for multi-modal ultrasound guidance that are intuitive for a non-specialist to use while scanning and trustworthy. You will work with clinical domain