64 parallel-and-distributed-computing-"Meta"-"Meta" positions at Cranfield University
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Development The successful candidate will be enrolled in Cranfield’s bespoke researcher training programme , gaining key skills in experimental design, data analysis, scientific communication, and professional
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suit candidates with a sound background in engineering, computer science, or related disciplines. Funding This is a self funded opportunity. Find out more about fees here. Diversity and Inclusion
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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should have an equivalent of a 1st or 2:1 UK honours degree or MSc degree (Distinction/Merit) in engineering, computer science, or other closely related fields. Experience with ROS and proficient
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benefit from an enhanced stipend of £25,726 per annum, undertake an international placement, and complete a bespoke training programme within a cohort of up to 15 students. Students will benefit from being
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are part of the programme. The research is funded by the Centre of Propulsion and Thermal Engineering at Cranfield University. The work will be conducted at the Cranfield icing wind tunnel (IWT) based
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in our CDT program, and warmly encourage applications from students of all backgrounds, including those from underrepresented groups. We particularly welcome students with disabilities, neurodiverse
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and grow with us. This role will lead to the successful completion of an apprenticeship development programme leading to a Level 3 Multi-Channel Marketer Apprenticeship. About You We are looking
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at international conferences and build a professional network across academia and industry. Development of expertise in cutting-edge experimental techniques, computational modelling, and interdisciplinary
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves