Prostate cancer (PCa) is the second most common cancer in men worldwide and ~307,000 men die every year. We know that infectious agents, such as bacteria and viruses, are involved in the development of a variety of cancers such as cervical, stomach, and bladder cancer. The causes of PCa and the development of advanced disease remains obscure, but there is good evidence that infectious agents could be one cause.
In this project you will examine the question of how infectious bacterial agents are involved in the development of PCa, or whether their presence is opportunistic. You will sequence and identify potentially novel bacteria that are associated with a poor outcome. You will determine the associations between bacteria, aggressive disease, and human cancer cell changes by mining existing cancer and urine datasets. You will investigate mechanisms of action between host and bacteria.
This research has the potential to reveal how bacteria can be used to predict the best treatment to receive and reveal new treatment possibilities to prevent or halt aggressive cancer.
This is a combined bioinformatics and lab experiment-based PhD. As part of the MMB DTP you will be able to take advantage of extensive training in microbial bioinformatics, lab skills for sequencing and molecular microbiology. During the PhD you will also gain skills in cancer biology, human ‘omics, “Big Data”, high performance computing, and statistical analyses. You will also be able to experience being involved in international consortiums.
You will be part of the Cancer Genetics team at the Norwich Medical School, which is an interdisciplinary team comprising a mixture of bioinformaticians, lab-based scientists, and clinicians. We have a broad interest in translational cancer based molecular studies with the aim of improving patient care. Research includes bacteria in cancer studies, urine-based biomarker development, whole genome sequencing studies, and cancer-subtype detection.
The Microbes, Microbiomes and Bioinformatics (MMB) Doctoral Training Partnership (DTP) is open to UK and international candidates with an undergraduate degree relevant to the scope of the programme for entry in October 2022 and offers postgraduates the opportunity to undertake a 4-year PhD research project funded by the UKRI Medical Research Council to advance the training of students in microbiology, with an emphasis on microbial bioinformatics.
The distinctive training offered by the programme aims to ensure that students feel comfortable running sophisticated computer analyses alongside laboratory work whilst enhancing problem-based learning in microbial bioinformatics and professional development and research skills through a comprehensive training programme. All students will undertake a Professional Placement lasting up to 12 weeks.
This project has been shortlisted for funding by the MMB DTP programme. Interviews for shortlisted candidates will take place on Tuesday 15 February or Wednesday 16 February 2022.
This MMB DTP is committed to equality, diversity, widening participation and inclusion in all areas of the programme. We encourage enquiries and applications from all sections of the community, regardless of gender, ethnicity, disability, age, sexual orientation, and transgender status. We value an aptitude for computer-based analysis, curiosity, and independence of thought, plus a commitment to work across the boundaries between the laboratory and bioinformatics to deliver high-impact research. We welcome applicants from low- and middle-income countries.
For information on eligibility and how to apply: https://www.uea.ac.uk/research/research-with-us/postgraduate-research/latest-phds-and-research-studentships/partnerships-in-doctoral-training
This project is awarded with a 4-year Microbes, Microbiomes and Bioinformatics (MMB) Doctoral Training Partnership (DTP) PhD studentship. Studentships include support for:
Studentship funding will not normally cover costs associated with visa or health surcharges, or additional costs associated with entry to, and living in the UK.
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