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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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/Associate at Theme 4, you will be expected to engage in collaborations across themes and identify funding opportunities. You will provide expertise in quantitative, qualitative and/or mixed-methods research
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challenge, making energy-efficient computing a critical research priority. This project addresses this challenge through a novel co-design approach that simultaneously optimizes both hardware and software
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. The developed technology will be rooted in causal reasoning, and we envision leveraging causal generative AI methods to develop a rigorous and comprehensive AI testbed. Clinical applications include, but are not
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development and refinement accordingly. We are looking for a highly organised, driven, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods
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methods to improve the deployment, adaptation capabilities and safety of robots and critical infrastructures. The developed algorithms will be evaluated on legged robots, wheel-based robots and under
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, and dynamic individual who is a team worker, has a positive outlook, and is adaptable and flexible in their working methods. It is also essential that you are highly experienced in setting up continuous
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effective lines of communication with all team members The candidate should have a PhD in molecular or cell biology, or a closely related discipline, or equivalent research, industrial or commercial
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methods and analytical tools in Africa and Asia. Our protocols and software will be available to the community to allow wider testing and sustained implementation. A critical part of WaSPP research agenda
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of conducting educational research. To thrive in this role, you will need: Experience of conducting qualitative or mixed-methods research, including interviews, focus groups, and literature reviews. Proficiency