CoMoBio: computational modelling of the formation of biofilm microbial systems
Interdisciplinary PhD opportunity for computational modelling of the formation of biofilm microbial systems.
Start date1 October 2022
Funding sourceEPSRC Doctoral Training Partnership
Enhanced EPSRC stipend (£19,062 per annum for 2022-23, with annual increments based on inflation) and fees covered. Funding also includes a research training and support grant of £3,000 for the duration of the studentship
Biofilms are complex communities of bacteria that adhere to a surface, and they are the oldest form of life recorded on this planet. They have significant potential for bioengineering applications, including for instance wastewater treatment or the production of alternative energy sources. On the other hand, they also constitute a serious global health concern, as they are the source of many types of infections. Indeed, bacterial infections are among the most common human illnesses.
A deeper understanding of the characteristics and dynamics of biofilm development could support the generation of desired biofilms and reduce the negative effects of undesired biofilms. However, the formation of biofilms is a complex and multi-step process involving different types of co-operating bacterial species. It involves interactions between biological behaviours, such as cell division and secretion of substances, and physical processes such as mechanical interactions and diffusion of chemicals. Due to these complexities, computational modelling has become an attractive and powerful tool to study the formation of biofilms.
In this project, the student will use innovative computational modelling (so-called agent-based modelling) to simulate the detailed formation of biofilms. In particular, the spatial distribution of different bacterial species and their functional integration within heterogeneous communities will be investigated. To this end, the student will work together with experts in the field to learn computational modelling methodologies, as well as the underlying biological and physical processes. In particular, the goals of this project are:
- Analyse experimental data from lab-grown biofilms
- Develop agent-based computational models to reproduce and predict experimental results using an open-source software platform (BioDynaMo) designed to easily create, run, and visualise 3D agent-based simulations
- Contribute to the ongoing computational biology collaboration BioDynaMo.
The University of Surrey and our collaborative partners provide a vibrant, interdisciplinary research environment, with access to state-of-the-art facilities. We see our postgraduate researchers as an integral part of our research community, collaborating and innovating together with academics at all levels. We want the most talented researchers from diverse backgrounds to join us, bringing new ideas and perspectives. We will help you make the most of your potential, removing barriers where we can and supporting you with dedicated career guidance. We offer generous funding packages, sector-leading researcher development training and mentoring, and dedicated employability support.
Whatever your aspirations, Surrey is where research careers are launched and nurtured.
Applicants must have a Bachelor's degree in physics, mathematics, computer science, bioinformatics or a related field. Academic excellence should be demonstrated, i.e. 2:1 or above. A masters degree and/or experience in computational biology are desirable but not essential. Basic skills in a relevant programming language, for example, C++ or Java or Python desirable but the key requirements are an interest in the topic and a good work ethic.
English language requirements
IELTS Academic: 6.5 or above (or equivalent) with 6 in each individual category.
How to apply
Applications should be submitted via the Computer Science PhD programme page on the "Apply" tab (select October 2022 start date). Please clearly state the studentship title and supervisor on your application. Once you have completed and submitted your application, please send an email to the primary supervisors confirming you have applied.
PhD Computer Science
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