MRC Laboratory of Molecular Biology
3 weeks ago
PhD in Machine Learning for Finding Macromolecules in Cells Medical Research Council Laboratory of Molecular Biology in United Kingdom
Degree Level
PhD
Field of study
Computer Science
Funding
Competition funded PhD project for students worldwide. Funding details beyond funded status are not specified in the post.
Deadline
Dec 8, 2026
Country
United Kingdom
University
MRC Laboratory of Molecular Biology

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About this position
PhD opportunity: Machine learning for finding macromolecules in cells at the Medical Research Council Laboratory of Molecular Biology (Cambridge, United Kingdom).
This project combines machine learning, artificial intelligence, and structural biology to develop computer software for identifying macromolecular complexes in cryo-EM and cryo-electron tomography (cryo-ET) data collected from thinned human and budding yeast cells. The main biological target is the kinetochore, with methods intended to be useful for other rare complexes in cells.
The research sits in a group studying chromosome segregation in mitosis, centromeres, and kinetochore structure/function. The post describes prior work using single-particle cryo-EM and current efforts to visualize kinetochores in situ using cryo-ET and zero-tilt cryo-EM. A key challenge is detecting kinetochores in dense nuclear chromatin, where existing 3D template matching approaches have not succeeded.
Eligibility highlights: applicants should understand AI/ML methods, be proficient in programming (for example Python), and be interested in structural biological questions. The listing is marked as a competition funded PhD project and is open to students worldwide.
Application: register your interest via the FindAPhD page. The university will respond directly.
Deadline: 2026-12-08.
Funding details
Competition funded PhD project for students worldwide. Funding details beyond funded status are not specified in the post.
What's required
Applicants should have a good understanding of AI and machine learning tools, be proficient in computer programming such as Python, and be interested in structural biological questions.
How to apply
Register your interest through the FindAPhD page. The university will respond directly, and you need a FindAPhD account to view enquiries and receive updates.
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