About the Project
The collaboration between Regan and Goddard seeks to move beyond the current experimental ‘trial and error’ approach to preparation of such matrices (hydrogels). In this project, the student will develop a modelling hierarchy for hydrogel formation, including numerical implementations and mathematical analysis of appropriate limits. The close collaboration between the Regan and Goddard labs will allow us to test model predictions experimentally. Ultimately, we will develop a predictive model for these hydrogels, which will enable us to design new materials, whose properties are specified a priori. We will thus be able to precisely fine-tune the design of the matrices so they are optimal for the growth and differentiation of different cell types. Thus, work will have an enormous impact in the area of precision regenerative medicine. We collaborate with the laboratory of David Hay (CRM), a liver regeneration expert. Through this collaboration we will be able to test the hydrogels in realistic applications as matrices for cell growth and differentiation.
The student will be a member of an interdisciplinary research community. Being part of the Precision Medicine cohort, they will gain a deep understanding of the potential scope and application of modeling in experimental biomedical research. The Regan group is experimental and interdisciplinary. In working on a collaborative project with the Regan and Goddard groups, the student will gain a deep understanding of the importance of a strong and reciprocal interplay between modeling and experiment. The student will be a member of the Applied and Computational mathematics theme, with associated opportunities to attend relevant seminars and research events, including presenting their research. They will learn a range of modelling techniques, both discrete and continuous, alongside the associated computational methods and underlying theory. They will interact with students in the MAC-MIGS CDT, an EPSRC-funded PhD programme in mathematical modelling, analysis and computation. Additional opportunities to enhance their professional skills will be via participation in public engagement activities with the Goddard and Regan laboratories.
This project is well-suited to students with undergraduate or masters degrees in applied mathematics, or a related subject, which includes mathematical modelling, who have an interest in applying their expertise in the Precision Medicine setting. Students with backgrounds in the biological and physical sciences, who have a strong interest in quantitative approaches are also encouraged to apply.
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.
For more information about Precision Medicine visit:
Qualifications criteria: Applicants applying for an MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area. The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,285 (UKRI rate 2020/21).
Full eligibility details are available: http://www.mrc.ac.uk/skills-careers/studentships/studentship-guidance/student-eligibility-requirements/
Enquiries regarding programme: [Email Address Removed]
 The past, present and future of protein-based materials (2018) NC Abascal, L Regan Royal Society Open Biology 8:180113
 PDE-constrained optimization models and pseudospectral methods for multiscale particle dynamics (preprint, 2020), M. Aduamoah, B. D. Goddard, J. W. Pearson, J. C. Roden, arXiv, http://arxiv.org/abs/2009.09850
 Nascent Transcript Folding Plays a Major Role in Determining RNA Polymerase Elongation Rates (2020) Tomasz W Turowski, Elisabeth Petfalski, Benjamin D Goddard, Sarah L French, Aleksandra Helwak, David Tollervey. J. Mol. Cell 79:488-503
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