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Field
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such as: Causal inference and the design and analysis of experiments Reinforcement learning and sequential decision-making Analysis of complex systems, networks, and large-scale data Machine learning
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synthetic ones. The Genomics group develops AL/ML methods to interpret genomes and distill the immensely complex networks that form the foundation of human biology and disease. Current areas of interest
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battery fire combustion and spread. Strong skills in turbulence modelling, CFD mesh generation in complex 3D geometries. Proficient in handling large data sets and the ability to analysis and interpret
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contribute to both pre-clinical and clinical studies—including major clinical trials and the Peripheral Vascular Biobank. You will lead complex research activities, support ethics and governance submissions
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performance guarantees, addressing several pressing challenges in contemporary streaming data scenarios, such as evolving baselines and complex, data-intensive settings. The applicant must master theoretical
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in securing research funding is essential, as is demonstrable expertise in complex modelling techniques such as machine learning, network neuroscience, or related computational approaches. You will
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Fellow, you will: Conduct qualitative and quantitative data analysis, including qualitative coding, mixed-methods analysis, and/or network mapping as appropriate. Manage and ensure the ethical handling and
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be part of a collaborative, interdisciplinary team working across the UK and EU, with access to real-world pilot sites and a network of academic, industry, and community. The Role: As a Research Fellow
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to communicate with clarity on complex information. Excellent communication skills in Chinese is a plus. Ability to build relationships and collaborate with others, both internally and externally. About Us Join a
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systems and cyber-physical integration; Knowledge of digital twin tools such as Unity, Unreal Engine, Siemens NX, and MATLAB Simscape; Ability to represent complex kinematic and dynamic models, including