739 phd-in-architecture-interior-design-built-environment Postdoctoral positions in Uk
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Postdoctoral Research Assistant in Design for Behaviour Change: Circular Economy for Medical Devices
of these solutions. You should possess a relevant PhD/DPhil (e.g. in Design, Business, Engineering or a related discipline) and sufficient specialist knowledge in the discipline to work within the established research
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This post is full time and has funding available until 30th September 2026 We are seeking to appoint a Community Innovation Practitioner to join the Health Economics and Health Technology
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Contract Type: Fixed-Term - 36 Months Do you have a passion for the built environment and have solid post graduate research experience in this area? Do you have specialist knowledge in thermal
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learning experiences within real-world environments. Through strategic partnerships forged by our faculty with industry, learners bridge theoretical knowledge with practical application in and out
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inference in engineered systems, including telecom networks; The development of neuromorphic algorithms and spiking neural models with built-in efficiency and reliability guarantees; The design of reliability
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to the overall architecture of the project’s wireless neuromodulation system. About You You will have: A PhD (or equivalent) in Electrical Engineering, Electronics, Electromagnetics, Bioelectronics, or a related
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techniques—including vision-language architectures (e.g., CLIP, BLIP), fine-tuning large language models for clinical NLP, and self-supervised contrastive learning—the models will learn to effectively combine
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. You will be based at our School of Engineering and Built Environment, with opportunities to carry out pilot-scale work and technology demonstrations at Glass Technology Services Ltd in Sheffield and
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University’s School of Engineering and Built Environment, with opportunities to carry out pilot-scale work and technology demonstrations at Glass Technology Services Ltd in Sheffield and short research visits
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lead the development of multi-modal MRI foundation models that integrate imaging data and radiology reports. Using advanced deep learning techniques—including vision-language architectures (e.g., CLIP