MRes Computational Cell Biophysics
At the forefront of interdisciplinary research.
Are you a physicist, a biologist, a chemist, a computer scientist, or a mathematician interested in interdisciplinary research? This course is for you!
Interdisciplinary approaches are rapidly being recognised as essential to address complex global challenges and drive forward scientific innovation. The Computational Cell Biophysics MRes is an innovative, research-focused course designed to provide students with key computational, analytical, and data science skill sets. Students will undertake a major research project in a world-leading lab, integrating skills from physics, maths and computer science with biology, to explore problems ranging from molecular processes to multicellular, tissue, organ or whole-organism dynamics. Students will learn image and data analysis, machine learning, statistical modelling, multiscale simulation, and AI approaches, key skill sets that are in high demand by employers, from academia to industry.
We aim to train flexible, multi-faceted researchers representing the next generation of scientists and entrepreneurs.
Programme overview
- Innovative and interdisciplinary
- 9-month lab-based projects in world-class research groups
- Students will learn essential programming and machine-learning skills
- Students will learn to communicate across disciplines
- Prepares graduates to pursue diverse careers in academia and industry
We are strongly committed to developing an inclusive and positive research culture and providing students with the support they need to succeed.
The programme consists of a 9-month research project and two other compulsory modules. In addition, students select two optional modules from the list below. Previous coding experience advantageous but not required. If students need additional training in biology or coding, they can choose to attend additional tutorials.
MRes Laboratory-Based Research Project in Biophysics (120 credits). Students will be given a diverse choice of projects offered by invited scientists across a wide range of UCL faculties. Each project will have two supervisors, one from the physical sciences and one from the biological sciences. Each project will be designed to address a fundamental biological problem.
Research Techniques in Cell Biology and Biophysics (15 Credits). The MRes module will combine attending seminars from visiting scientists to UCL research departments, tutorials in cutting edge research techniques, with visits to UCL’s world leading facilities for imaging, high-content screening, bioinformatics, computation, nanotechnology, and material science.
Computational Cell Biophysics (15 Credits). Research-led teaching by scientists at the forefront of the biophysics research field provide students with a conceptual and quantitative understanding of areas of physics that are relevant to biology.
Advanced Molecular Cell Biology (CELL0016, 15-Credit)
Tissue Biology (CELL0024, 15-Credit)
Interdisciplinary Cell Biology (CELL0017, 15-Credit)
Advanced Practical Cell Biology (CELL0022, 15-Credit)
Cell Signalling in Health and Disease (PHOL0008, 30-Credit)
Applied Deep Learning (COMP0197, 15-Credit)
Machine Learning in Medical Imaging (MPHY0041, 15-Credit)
Computational Modelling for Biomedical Imaging (COMP0118, 15-Credit)
Machine Learning for Data Science (CEGE0004, 15-Credit)
Genomics and Drug Development (GENE0008, 15-Credit)
- AI approaches to learn context-specific representations of protein function
- Computational designs of novel proteins to engineer ligand-receptor specificities and rewire signalling cascades
- Coarse-grained molecular dynamics modelling of collagen networks
- Modelling the perturbation of membrane dynamics with antimicrobial peptides
- Inferring molecular programs from single-cell transcriptomic atlases
- Vertex modelling of lymph node dynamics during homeostasis and disease.
- Learning biophysical determinants of cell shape with deep neural networks.
- Computer vision and machine learning to determine 3D cell shape in complex epithelia
- 3D mechanical modelling of effects of microgravity on tissue growth and repair
- Mathematical modelling of cell migration in self-generating gradients
- Modelling the mechanical evolution of the apical domain during differentiation of iPSCs into neuroepithelial cells
- Mathematical modelling of the role of calcium signalling in determining embryonic polarity
- Modelling morphogen gradient formation during growth and morphogenesis
- Inferring model parameters from experimental data
- Robotic artificial Selection of microbial communities
- Simulating artificial selection of microbial communities
- Understanding immune system group chemotaxis using microscopes and mathematical modelling
Application details
Who can apply:
- Admits students from all sciences
- UK and international students can apply
Find out about funding your studies here.
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Find out about Computational Cell Biophysics MRes modules, career prospects, entry requirements, fees, and how to apply for this course.
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