Research Assistant/Associate in AI for Materials and Manufacturing (Fixed Term)

CamWebDir; Cambridgeshire and Peterborough; Remote; GBP 33,000 - 46,000; Full time

Job summary

The University of Cambridge, Department of Engineering, seeks a Research Assistant/Associate in AI for Materials and Manufacturing on a fixed-term basis to develop uncertainty-aware digital twin and AI control architectures for advanced materials processing.

The role involves multidisciplinary collaboration across protein design, nanocrystal synthesis, flow chemistry, printing, and scale-up, with an emphasis on machine learning for materials informatics and process optimization.

Qualifications

• PhD in engineering, CS, math, data science or related field.
• Strong ML/statistical modelling for physical systems.

Responsibilities

• Develop uncertainty-aware digital twin and AI control architecture.
• Integrate descriptors, models and metrology for process control.
• Support data sharing, model interfaces and reports.

Skills

ML/Stat modelling

Scientific programming

Data workflows

Collaboration

Education

PhD (near completion)

Tools

Python

MATLAB

R

Job description

# Research Assistant/Associate in AI for Materials and Manufacturing (Fixed Term)UUniversity of CambridgeCB2 1TNvia University of CambridgePosted 6 Oct 2026Apply on cam.ac.uk →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 technologiesThe 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 - £46,049Fixed-term: The funds for this post are available until 31 December 2027 in the first instance.Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.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 ([e-mail]) or Holly Shaw ([e-mail]).Please quote reference NM51326 on your application and in any correspondence about this vacancy.