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for Postdoctoral Researchers/Research Fellows in the following areas: Areas of interest: Privacy and Compliance, User Experience; Computational Data Science and Applications; High-performance, Energy-efficient
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A position exists, for a Research Assistant/Associate in the Department of Engineering, to work on Data Science for Construction Productivity. The researcher's responsibilities will include
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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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the combined themes of human-computer interaction and critical computing. The lab will be exploring the notion of "deceptive by design" on all fronts: social identity cues in the design of LLM-based chatbots
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We are seeking a research assistant with a background in computing to develop AI models for image reconstruction from data from our ultra-thin fibre-based spatial frequency domain imaging device
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees
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, as well as for their babies. You will work with large, complex datasets from national surveys and routinely collected health data to support impactful research. You will manage your own research
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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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involves qualitative data collection with people living with brain tumours, their communication partners, speech and language therapists (SLTs), and other healthcare professionals. Stage 2 uses co-design
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, and interactions with horizontal water flows. This work will be underpinned by in situ observations of GHG fluxes and hydrological information made by other members of the CLR team across the three CLR