About the Project
The group will be co-located at the School of Biological Sciences and School of Informatics of the University of Edinburgh. This will give us privileged access to cutting-edge biological research at Edinburgh, as well as its world-leading expertise in machine learning and data science. Our students will benefit from this unique synergy and also enjoy the thriving ecosystem of SynthSys – the Edinburgh Centre for Systems and Synthetic Biology.
The project will focus on the dynamics of metabolic pathways coupled with gene regulation using a mix of nonlinear dynamics and various approximation techniques . We will apply the theoretical results to metabolic engineering for chemical production  and the design of synthetic microbial communities with mechanistic ‘whole-cell’ models .
Ideal candidates should have excellent academic record and passion for quantitative methods in the life sciences and medicine. We seek open-minded and creative students keen to join a multidisciplinary team. You should have excellent mathematical and computational skills, as well as outstanding presentation skills for various audiences. Applicants must hold a First Class or an Upper Second Class degree (or equivalent overseas qualification) in a discipline relevant to the project, such as Mathematics, Bioengineering, Biochemistry, Computer Science, Physics, or Control Engineering.
If you would like us to consider you for one of our scholarships you must apply by 12 noon on 13 December 2018 at the latest.
 Beguerisse-Díaz et al (2018). Flux-dependent graphs for metabolic networks. NPJ
Systems Biology and Applications
 Liu et al (2018), Dynamic metabolic control: towards precision engineering of metabolism,
J Industrial Microbiology & Biotechnology
 Weisse, Oyarzún, Danos & Swain (2015) Mechanistic links between cellular trade-offs,
gene expression, and growth, PNAS
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