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industry stakeholders through collaborative research and contract work. Prior experience managing an analytical services program or conducting industry-relevant research is highly desirable. Responsibilities
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contact: Prof. Eduard Hryha, director of CAM2 and topic leader: hryha@chalmers.se Prof. Uta Klement, head of Division of Materials and Manufacture: uta.klement@chalmers.se We look forward to your
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. Industrial Sponsorship The PhD is fully funded through the EPSRC ICASE scheme and supported by BAE Systems, offering strong industrial relevance and collaboration. The student will be based at Cranfield
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Intelligence (AI) is increasingly being integrated into project-based work across industries, with the potential to transform how projects are conceived, planned, and delivered. Despite growing interest
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | about 1 month ago
the Centre for Doctoral Training in Green Industrial Futures (CDT-GIF ). We are offering pioneering research projects that will enable PhD researchers to explore key technologies and solutions that will
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Edinburgh, Scotland | United Kingdom | about 1 month ago
the Centre for Doctoral Training in Green Industrial Futures (CDT-GIF ). We are offering pioneering research projects that will enable PhD researchers to explore key technologies and solutions that will
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. You will investigate existing approaches to Systems Engineering at our industrial partners Canon Production Printing, Rademaker Industrial Bakery Equipment and VMI machinery. Building
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, supporting AI-powered electronics research. This project will be conducted within Cranfield’s Integrated Vehicle Health Management (IVHM) Centre, established in 2008 in collaboration with industry leaders
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to leverage high-throughput phenotyping to create knowledge about plant function at the physiological level and use forward genetics approaches to unravel the genetic architecture of root traits. Our most
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The project: The deployment of generative AI—particularly Large Language Models (LLMs) based on transformer architectures—in industrial settings poses several critical challenges. Ensuring reliable