Manufacturing is responsible for 1/3rd of global economic output, 20% of global carbon emissions, and consumes 54% of global energy resources. Integration of AI advances into manufacturing will therefore have enormous global impact. This is a CASE type award with Matta, a Cambridge spin-out of which Dr. Pattinson is co-founder. Matta is a group of engineers, scientists, and builders developing manufacturing foundation models (MFMs) and a general-purpose manufacturing OS to improve the sustainability of manufacturing today and to unlock the unimaginable technologies of tomorrow.
The project seeks to revolutionise design and manufacturing end-to-end, by enabling the conception, optimisation and production of better products. As a starting point, this will focus on "neural" digital twins, powered by data sources including process monitoring, supply chains, literature and human expert input. By creating a dynamic, real-time replica of parts being manufactured, these digital twins could drive unprecedented gains in manufacturing capability and sustainability by enabling real-time simulation, optimization, and predictive maintenance. This is a rapidly evolving field and so we expect that the research direction and methods will adapt to ongoing discoveries.
The student will benefit from extensive computing and hardware resources including the University of Cambridge's cluster of 320 A100 GPUs and further capacity through Matta. The student will also have access to unique data and extensive relevant expertise through collaboration with Matta's research team. This will also present unique opportunities to publish work across academia and industry.
Minimum Requirements
Applicants should have (or expect to obtain by the start date) at least a good 2.1 degree in Computer Science, Mathematics, Electrical or Mechanical Engineering or a related subject.
Application Process
To apply for this studentship, please send your CV, cover letter and academic transcripts to Dr. Sebastian Pattinson (swp29@cam.ac.uk) to arrive no later than 1st February 2025. Early application is strongly encouraged as applications will be reviewed upon receipt and selection may be made before the deadline.
Please note that any offer of funding will be conditional on securing a place as a PhD student. Candidates will need to apply separately for admission through the University's Graduate Admissions application portal; this can be done before or after applying for this funding opportunity. The applicant portal can be accessed via: www.graduate.study.cam.ac.uk/courses/directory/egegpdpeg. The funding is conditional on submitting this application before 31 March 2025.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
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Building AI copilots for advanced manufacturing
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