University College London Featured PhD Programmes
Engineering and Physical Sciences Research Council Featured PhD Programmes
FindA University Ltd Featured PhD Programmes
University of Sheffield Featured PhD Programmes
University of Reading Featured PhD Programmes

Metabolic modelling of biofilms in a mixed population

This project is no longer listed on and may not be available.

Click here to search for PhD studentship opportunities
  • Full or part time
    Dr C Angione
  • Application Deadline
    No more applications being accepted
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

About This PhD Project

Project Description

PhD Fully-Funded Studentship
Studentship code IIIP0005
School of Computing and Digital Technologies
Teesside University and Complement Genomics

This PhD studentship opportunity is offered through the Intensive Industrial Innovation Programme (IIIP). The IIIP Programme is a collaboration between Northumbria, Durham, Newcastle and Teesside Universities, receiving up to £2,202,411 of funding from the England European Regional Development Fund (ERDF) as part of the European Structural and Investment Funds Growth Programme 2014-2020. The Ministry of Housing, Communities and Local Government is the Managing Authority for ERDF. Established by the European Union, ERDF funds help local areas stimulate their economic development by investing in projects which will support innovation, businesses, create jobs and local community regenerations. For more information visit

PhD topic: Metabolic modelling of biofilms in a mixed population

Project Outline

Changes in microbiomes have been recently linked with major impacts on human health. Furthermore, sequencing studies can elucidate the abundance of the species with high accuracy. The large number of species and biological components involved in these microbiomes, coupled with their highly dynamic behaviour, make it difficult to extract information from available biological samples. Another major challenge is that such populations are often mixed (bacteria and fungi).

We therefore propose to leverage state-of-the-art tools in metabolic modelling (Magnúsdóttir et al., Nature Biotechnology, 2017) with the goal of augmenting the available data collected by Complement Genomics and explaining biofilm behaviour from a mechanistic point of view, towards a mixed- and multi-species genome-scale metabolic model of the microbiome. Both steady-state and dynamic approaches will be explored (Zhang et al., bioRxiv, 2018), with the idea of combining them towards a dynamic multi-scale model (Henson et al, Biochemical Society Transactions, 2015). The biofilm architecture (considering spatial arrangement, thickness, viability) will be also studied and taken into account. Data analytics and machine/deep learning techniques will be also used to simulate the model and interpret the data, enabling comparison of the biofilm behaviour in various conditions.

For this project, machine/deep learning techniques and multi-objective optimisation algorithms will be used in combination with biomedical modelling. Complement Genomics Ltd will provide microbiomic data sets for use in this project and which are of relevance to the human condition.

Funding and Eligibility

Applications are welcome from strong UK, EU and International students. The studentship covers tuition fees at the Home/EU rate for three years and provides an annual tax-free stipend of £15,000 p.a. for three years, subject to satisfactory progress. Non-EU International students will be required to pay the difference between the Home/EU and International fee rate.

Entry Requirements

Applicants should hold or expect to obtain a relevant degree at 2.1 minimum, or an equivalent overseas degree in Bioinformatics, Mathematics, Engineering, Physics, Computer Science or a closely related subject. Good programming skills are desired. Previous experience in general mathematical or biomedical modelling is also desired, but not essential. International students would be subject to the standard entry criteria relating to Tier 4 visa procedures English language ability and ATAS certification.

About Teesside University

Teesside University is delighted to be able to offer a number of part-funded industrial PhDs to eligible SMEs in the North East. This project is funded by the University and European Regional Development Funding and looks to support local firms with their research and development needs, developing new products and services in key sectors and creating high-quality jobs in the local economy. North East England’s universities are joining forces under a £3.9m scheme, funded by the European Regional Development Fund, to connect the region’s businesses with research to encourage growth and job creation. The Intensive Industrial Innovation Programme (IIIP) will see Durham, Newcastle, Northumbria and Teesside universities work directly with small and medium-sized enterprises (SMEs) in the region to develop new services and products for the market.

The School of Computing and Digital Technologies at Teesside University conducts research on a wide range of topic areas including Computer Science, Computational Biology, Artificial Intelligence, Software Engineering, Programming, Cyber-Physical Systems, Computer Games, Animation and Media. In REF 2014, 69.8% of our research outputs in Computer Science and Informatics was recognised as world-leading or internationally excellent. More information -

The Tees Valley is an enjoyable place to live – in the heart of the North of England’s coastline and countryside, with easy access to Durham, Newcastle and York.

About Complement Genomics

Complement Genomics ( is an innovator in genetic testing technologies. They were the first to truly take DNA testing to the general public via and continue to bring forward new and improved DNA testing services. They have considerable expertise in genotyping and other types of molecular biology services and also carry out our own research programmes, most notably in the area of biomarker assay development and validation. They work though branded services each of which serves a different market segment. They are based at the
Durham Genome Centre -

How to Apply

You can apply online for this opportunity (; please use the Full Time Funded PhD full time online application form, and select “Studentship” when asked to specify funding. The studentship code “IIIP0005” should be clearly indicated on the application and any materials submitted. Applications that do not include this code may not be considered for the correct funding.

Academic enquiries:

ERDF enquiries: Jennifer Hudson ([Email Address Removed]), Rachel Frampton ([Email Address Removed])

Academic enquiries: Dr Claudio Angione ([Email Address Removed])

Closing Date: 9am 23 July 2019. We envisage that interviews will take place in early August. The successful applicant must be prepared to start on 7 October 2019. The conditions of the funding do not permit for a later start date.

FindAPhD. Copyright 2005-2019
All rights reserved.