Computational systems biology of B-cell lymphoma

Applications are invited for a 3-year PhD studentship to join Brighton and Sussex Medical School at the University of Sussex Campus.
The project aims to create simulations of B-cell lymphomas that can be used to perform virtual experiments, reveal the molecular mechanisms leading to lymphoma and find promising new targets for therapy. These models will be explained and be validated by clinical and experimental results from existing literature and international collaborators.
B-cell lymphomas are a commonly occurring cancer occurring when mutations cause a loss of regulation of molecular pathways controlling cell survival, proliferation and differentiation. While lots is known about the mutations that cause B-cell lymphomas finding better therapies to treat these cancers requires improving our understanding of how dysregulation of molecular signalling pathways leads to cancerous cell fates (1).
This studentship will be with Simon Mitchell, who recently established his group using computational systems biology approaches to investigate lymphoma at BSMS. We recently published computational simulations of how cell fates are altered by changes in molecular signalling networks and revealed new interactions and targets to control cell fate that were validated in the lab (2, 3). These models are systems of differential equations, which are written into computer code, and solved using computational solvers with populations of individual being solved with parallel processing (4, 5). Preliminary data show that if we recreate dysregulation found in B-cell lymphomas we can recreate the cell fate changes that lead to lymphoma.
We now want to extend this to work to create simulations of B-cell lymphomas that can be used to perform virtual experiments, reveal the molecular mechanisms leading to lymphoma and find promising new targets for therapy. The goal of this thesis will be to extend our existing models of B-cell fate decisions by combining published models in a variety of formats. Through developing a detailed knowledge of the molecular biology of B-cell lymphoma, the student will recreate in the model the dysregulation found in cancer. The simulations of B-cell lymphoma will be validated using publicly available data or by making predictions that can be tested in the lab. The student will use the models they create to predict effective ways to treat B-cell lymphoma.
We are seeking a highly motivated person to join a growing team of scientists at BSMS investigating blood cancers. The student will gain a wide range of interdisciplinary skills in computational systems biology including building and analysing computational models, writing code that helps answer challenging biological and clinic questions, collaborating with scientists and clinicians across disciplines and a broad academic publishing and presentation skillset. This training will make the student highly competitive for academic or industrial positions applying systems approaches to multiple disciplines.
Applicants for this 3-year funded PhD starting in April 2020 should possess or expect to be awarded a minimum of a First or Upper Second Class Honours degree (or equivalent) in Mathematics, Computer Science, Biochemistry, Biology, Bioengineering or a related subject. Experience coding in one or more programming languages is required. A-level mathematics or equivalent is required if undergraduate degree is in Biology. Molecular biology knowledge is desirable but the ability to learn the details of new systems to accurately simulate them is most important. Both UK/EU and non-EU citizens can apply (home fees will be paid for UK/EU citizens; non-UK/EU citizens will be liable for the difference in fees between the rate for home (EU) students and the overseas student rate). Informal enquiries should be directed to Simon Mitchell ([Email Address Removed]). In order to apply please visit the University of Brighton website. Please contact the BSMS Doctoral and Research Officer ([Email Address Removed]) for any queries not relating to the research.

References (see example below):

1. Schmitz R, Wright GW, Huang DW, Johnson CA, Phelan JD, Wang JQ, et al. Genetics and pathogenesis of diffuse large B-cell lymphoma. New England Journal of Medicine. 2018;378(15):1396-407.
2. Mitchell S, Hoffmann A. Identifying noise sources governing cell-to-cell variability. Current opinion in systems biology. 2018;8:39-45.
3. Roy K, Mitchell S, Liu Y, Ohta S, Lin Y-s, Metzig MO, et al. A Regulatory Circuit Controlling the Dynamics of NFκB cRel Transitions B Cells from Proliferation to Plasma Cell Differentiation. Immunity. 2019.
4. Shokhirev MN, Almaden J, Davis‐Turak J, Birnbaum HA, Russell TM, Vargas JA, et al. A multi‐scale approach reveals that NF‐κB cRel enforces a B‐cell decision to divide. Molecular systems biology. 2015;11(2).
5. Mitchell S, Tsui R, Hoffmann A. Studying NF-κB signaling with mathematical models. NF-kappa B: Humana Press, New York, NY; 2015. p. 647-61.