Constructing robust gene networks using a combined experimental and bayesian approach

The engineering of commensal microbiota through synthetic biology approaches has the potential to create novel therapeutics and diagnostic tools that could revolutionize medicine. To achieve this, we must build systems that function across a wide range of varying environmental and internal conditions, such as growth, stress response, temperature, and pH. It is known from theory that the addition of feedback mechanisms can increase system robustness.

Our goal is to construct novel gene networks incorporating feedback; initially we will focus on oscillators as these serve as a model for the construction of complex systems. Our approach will use mathematical modeling and Bayesian statistics to make predictions on how gene networks perform under varying conditions. We will then construct these systems to test our model predictions and demonstrate their robustness.

ELIGIBILITY AND APPLICATION
This four-year studentship is funded jointly by the Microsoft Research PhD Scholarship Programme and the BBSRC London Interdisciplinary PhD Programme. It covers UK/EU tuition fees and an annual tax-free stipend in the region of £16,057 (exact amount confirmed each year).
Applications will be considered from individuals with a background in life science or physical science (mathematics, physics, computer science), though the equivalent of a first or upper second-class degree is essential. A postgraduate degree in a relevant subject would be desirable, as would basic molecular biology skills, experience of computer programming (e.g. C, C++, Python, R, F#, or Matlab) and a demonstrable interest in synthetic biology.

For more information regarding the project, please contact Dr Chris Barnes - [Email Address Removed]
For more information about the programme, eligibility or the application process please contact the programme administrator - [Email Address Removed]