Location: West Cambridge
A position exists for a Research Assistant/Associate in AI for Materials and Manufacturing in the Department of Engineering, University of Cambridge, to work on a multidisciplinary research programme developing protein-guided, droplet-based routes to architected functional materials, as part of an Advanced Research + Invention Agency-funded project, subject to contract negotiations. The post holder will be located in West Cambridge, Cambridgeshire, UK.
The project, collaborating across seven research groups, delivers a new pathway and manufacturing process towards multi-functional architected materials across length scales, studying:
(i) how to create rare-earth free magnetic materials at scale and in useful formats
(ii) how to create advanced, nanoporous electrodes for high capacity, long-life battery technologies
The key responsibilities and duties are to develop the project's uncertainty-aware hybrid digital twin and AI control architecture. The appointee will combine protein and formulation descriptors, reduced-order or physics-informed droplet and deposition models, multimodal in-line metrology and process-structure-property machine learning. They will develop information-efficient experiment selection, diagnose process drift, recommend quantitative parameter corrections and support route down-selection and statistical process control.
The appointee will collaborate closely with researchers in protein design, nanocrystal synthesis, flow chemistry, printing, biomineralisation, advanced characterisation, magnetics, batteries and scale-up. They will help establish shared data and model interfaces, integrate multimodal in-line metrology, communicate uncertainty and model limitations, and contribute to reports, publications, presentations and programme stage gates.
Applicants must have (or be close to obtaining) a PhD in engineering, computer science, applied mathematics, physics, data science, materials science or a closely related discipline. Essential capabilities include machine learning or statistical modelling for physical systems, quantitative model validation, scientific programming and reproducible data workflows, and effective multidisciplinary collaboration. Experience in hybrid modelling, uncertainty quantification, active learning or optimisation, digital twins, process control, multimodal metrology data, materials informatics or advanced manufacturing is desirable rather than required across every area.
Appointment at Research Associate level is dependent on having a PhD.
Those who have submitted but not yet received their PhD will be appointed at Research Assistant level, which will be amended to Research Associate once the PhD has been awarded.
Salary Ranges:
Research Assistant £33,002 - £35,608;
Research Associate £37,694 - £46,049
Fixed-term: The funds for this post are available until 31 December 2027 in the first instance.
To apply online for this vacancy and to view further information about the role, please click 'Apply' above.
Please ensure that you upload your Curriculum Vitae (CV) and a covering letter in the Upload section of the online application. If you upload any additional documents which have not been requested, we will not be able to consider these as part of your application. Please submit your application by midnight on the closing date.
If you have any questions about this vacancy or the application process, please contact Prof. Ronan Daly () or Holly Shaw ().
Please quote reference NM51326 on your application and in any correspondence about this vacancy.
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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