We are looking for a motivated doctoral student to join us on an exciting project at the interface of stochastic modelling and systems and synthetic biology. Stochasticity is a hallmark of life at the molecular scale. Cells in a population display substantial variation, even when they are genetically identical. Such ’cellular noise’ emerges from the interplay of thousands of stochastic chemical reactions and is key in many biomedical challenges such as cancer progression or the emergence of drug resistance in dangerous pathogens.
In this project you will develop new methods for studying stochasticity in biochemical systems particularly those in mammalian cells. Starting from a Chemical Master Equation that describes the temporal evolution of the probability density function of molecule numbers, we will study the properties of its solutions with a combination of analytic approximation methods and stochastic simulations. The goal is to understand how the fluctuations in molecule numbers inside a cell depend on biochemical parameters and to hence elucidate the key mechanisms by which this noise is regulated. We will focus on mathematical models for stochastic gene expression of increasing complexity, including multiple timescales, complex spatial organization, cell division, gene replication and limitations in molecular resources typically found in synthetic biology applications – see references below for some examples of our latest work in the field.
The project will expose the student to cutting-edge multidisciplinary research at the interface of stochastic analysis and biological systems, with exciting opportunities for training and career progression. The successful candidate will join the group of Prof Ramon Grima (grimagroup.bio.ed.ac.uk) in collaboration with the Biomolecular Control Group led by Diego Oyarzún (homepages.inf.ed.ac.uk/doyarzun/). The student will also join the thriving ecosystem of SynthSys – the Edinburgh Centre for Systems and Synthetic Biology, one of the leading venues in the discipline.
The ideal candidate should have excellent mathematical and computational skills. 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 Physics, Mathematics, Bioengineering, Biochemistry, Computer Science, or Control Theory.
The “Visit Website” button will take you to our Online Application checklist. Complete each step and download the checklist which will provide a list of funding options and guide you through the application process. Follow the instructions on the EASTBIO website (you will be directed here from our application checklist), ensuring you upload an EASTBIO application form and transcripts to your application, and ticking the box to request references. Your referees should upload their references using the EASTBIO reference form, in time for the 5th January deadline so please give them plenty of time to do this by applying early.
 Cao, Filatova, Oyarzún & Grima, Multi-scale bursting in stochastic gene expression, submitted, preprint at www.biorxiv.org/content/10.1101/717199v1 , 2019
 Tonn, Thomas, Barahona & Oyarzún, Stochastic modelling reveals mechanisms of metabolic heterogeneity, Communications Biology, 2019
 Cao & Grima, Linear mapping approximation of gene regulatory networks with stochastic dynamics, Nature Communications, 2018.
How good is research at University of Edinburgh in Biological Sciences?
FTE Category A staff submitted: 109.70
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