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Location: Central Cambridge PhD Studentship - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based elaboration of biocatalysis
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that suppress resistance gene transfer. Combining biophysics, microbiology, and materials science, the project will generate insights into how physical environments can be harnessed to control AMR. Approach and
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students Subject areas Computer sciences Physical & Environmental Sciences Project description The accelerating impacts of climate change—particularly those related to water, such as flooding, coastal
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engineering, or atmospheric science* Expertise in and passion for computational modelling and software development/engineering Expertise in cloud physics or contrails preferred but not required Creative problem
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profile We welcome applicants with backgrounds in computer science, applied mathematics, or engineering. Essential: strong Python, deep learning experience (PyTorch), and foundations in calculus/linear
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(Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How to apply For information on how to apply, please click on the ‘Apply’ button
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applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply How to apply Please read and complete
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural
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within the Institute of Health Informatics. The studentships will commence from Feb 2026. About the project Successful applicants will work with the programme coordinator to identify a project and a
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good Master’s degree in Mathematics, Statistics, Computer Science, Engineering, Physics, with good programming, analytical problem-solving, writing and presentation skills. Please direct project specific