MRC DiMeN Doctoral Training Partnership: Building a virtual human embryo to predict developmental success and failure
Posted by the Node, on 5 November 2025
Location: Sheffield
Closing Date: 4 December 2025
About the Project
Unlocking the secrets of human embryo development demands a new, dynamic approach. This PhD project offers a unique opportunity to apply cutting-edge computational methods to a fundamental challenge in reproductive biology: understanding why human embryos fail. As delayed childbearing becomes more common, pinpointing the barriers to healthy development is critical. You’ll be at the forefront of this effort, transforming static biological observations into a dynamic, predictive, and virtual model of the human embryo.
Current knowledge of early human development is largely based on static snapshots. We lack a predictive framework to explain embryo-intrinsic failure. This project addresses that critical gap by hypothesizing that such failures occur at predictable developmental bottlenecks driven by intrinsic cell-to-cell variability and genetic factors.
Your core aims will be threefold:
1. Build a spatiotemporal lineage atlas of the pre-implantation human embryo using high-content 3D imaging.
2. Construct a data-driven virtual human embryo (an in silico model) by integrating this atlas with single-cell molecular data.
3. Identify when and why embryos fail using targeted computational perturbations.
This inherently interdisciplinary project lies at the intersection of developmental biology, computational science, and advanced data analytics. It is ideal for a student from a mathematics or physics background eager to move into biology, or for a biologist keen to gain advanced quantitative skills. You will receive comprehensive training in both computational and experimental methods.
Key techniques include: deep learning and image analysis with tools such as Cellpose-SAM for precise cell segmentation; quantitative data integration to fuse lineage-resolved 3D imaging with single-cell RNA sequencing (scRNA-seq) trajectories; agent-based and multiscale modelling using the Chaste computational platform to build the virtual embryo; and Bayesian Inference to calibrate model parameters and identify developmental control points.
You will also gain experience in the simulation-experiment loop, where computational predictions are tested in the lab – a highly sought-after skill in modern science.
The impact of this work extends beyond fundamental biology. By revealing the underlying rules of cell-fate change and identifying key developmental vulnerabilities, the virtual human embryo will serve as a powerful preclinical tool. The ultimate goal is to create a predictive framework to inform new clinical strategies – improving fertility treatments, enhancing embryo viability assessments, and shedding light on the origins of congenital conditions. You will be encouraged to practice open research and present your findings at international conferences, ensuring your discoveries rapidly benefit the global scientific community.
To find out more about the supervisors’ research groups, please visit our websites:
https://sheffield.ac.uk/mps/people/all-academic-staff/alexander-fletcher
Institutional entry requirements for PhD:
For entry into this PhD programme you should hold, or expect to hold, an honours degree in a related subject area with a 2:1 or first-class honours (or overseas equivalent). For applicants whose first language is not English, IELTS: 6.5, with no less than 6.0 in each component, or equivalent will be required unless exemptions apply. Please see the University of Sheffield website for full details: https://sheffield.ac.uk/mps/postgraduate/phd-opportunities/how-apply-your-phd#entry-requirements
How to apply: All applications are made via the application form accessed on the DiMeN website at https://www.dimen.org.uk/applications
Please read the full application guidance on the website before submitting an application.
Benefits of being in the DiMeN DTP:
This project is part of the Discovery Medicine North Doctoral Training Partnership (DiMeN DTP), a diverse community of PhD students across the North of England researching the major health problems facing the world today. Our partner institutions (Universities of Leeds, Liverpool, Newcastle, York and Sheffield) are internationally recognised as centres of research excellence and can offer you access to state-of-the-art facilities to deliver high impact research.
We are very proud of our student-centred ethos and committed to supporting you throughout your PhD. As part of the DTP, we offer bespoke training in key skills sought after in early career researchers, as well as opportunities to broaden your career horizons in a range of non-academic sectors.
Being funded by the MRC means you can access additional funding for research placements, training opportunities or internships in science policy, science communication and beyond.
Further information on the programme and instructions on how to apply, including a link to the application portal, can be found on our website
Funding Notes
Studentships are fully funded by the Medical Research Council (MRC) for 4yrs. Funding will cover tuition fees, stipend (£20,780 for 2024/25) and project costs. We have a very small number of funded studentships for exceptional international applicants. Please read additional guidance here: View Website
Studentships commence: 1st October 2026
Good luck!
References
2. Strawbridge SE, Kurowski A, Corujo-Simon E, Fletcher AN, Nichols J, Fletcher AG. insideOutside: an accessible algorithm for classifying interior and exterior points, with applications in embryology. Biol Open. 2023 Sep 15;12(9):bio060055. https://doi.org/10.1242/bio.060055
3. Johnson CGM, Fletcher AG, Soyer OS. ChemChaste: Simulating spatially inhomogeneous biochemical reaction-diffusion systems for modeling cell-environment feedbacks. Gigascience. 2022 Jun 17;11:giac051. https://doi.org/10.1093/gigascience/giac051
4. Guo G, Stirparo GG, Strawbridge SE, Spindlow D, Yang J, Clarke J, Dattani A, Yanagida A, Li MA, Myers S, Özel BN, Nichols J, Smith A. Human naive epiblast cells possess unrestricted lineage potential. Cell Stem Cell. 2021 Jun 3;28(6):1040-1056.e6. https://doi.org/10.1016/j.stem.2021.02.025
5. Cooper FR, Baker RE, Bernabeu MO, Bordas R, Bowler L, Bueno-Orovio A, Byrne HM, Carapella V, Cardone-Noott L, Jonatha C, Dutta S, Evans BD, Fletcher AG, Grogan JA, Guo W, Harvey DG, Hendrix M, Kay D, Kursawe J, Maini PK, McMillan B, Mirams GR, Osborne JM, Pathmanathan P, Pitt-Francis JM, Robinson M, Rodriguez B, Spiteri RJ, Gavaghan DJ. Chaste: Cancer, Heart and Soft Tissue Environment. J Open Source Softw. 2020 Mar 13;5(47):1848. https://doi.org/10.21105/joss.01848
Start date: 1 October 2026
Closing Date: 4 December 2025
Duration: Fixed term
