There is unprecedented potential to learn from existing patient data, such that we can diagnose new patients faster and more accurately define the specific molecular mechanism(s) underlying their disease.
This project will use computer science and programming skills to integrate digital healthcare and genomic data to develop and test informatic tools that guide clinical decisions resulting in better outcomes for patients.
The NHS Long Term Plan and Genomic Medicine Service commitments to harness genomic technology to improve the health of the population mean that we are world-leading in generating vast genomic data on patients with cancer and rare diseases. Working within trusted research environments, we now have the exciting opportunity to develop and optimise methods to integrate these genomic sequencing data with electronic healthcare records.
Working within the NIHR Southampton Biomedical Research Centre, the project sits within a digital ecosystem centred around translating cutting-edge tools and technologies to improve patient outcomes. The University of Southampton boasts a nationally leading compute cluster; University Hospital Southampton NHS Foundation Trust is recognised as a global digital exemplar. The project will test and implement novel genotype-to-phenotype bioinformatic approaches using AI techniques (knowledge inference and machine learning), on rich, real-world patient data.
The skills required
The successful candidate will have strong informatic skills (programming, mathematics, computer science) and be motivated to understand molecular mechanisms of genetic disease at the patient level. A keen grasp of genetics and sequencing technologies will be essential for effective processing and interpretation of genomic data. Sitting at the interface of computer science, medicine and genomics, effective communication with multidisciplinary colleagues will be essential. Applicants should be self-driven, have excellent organisational skills, and be motivated by the potential to impact the health of individual patients and their families.
The project applies informatic skills to large-scale biomedical data and so candidates should have or expect to obtain at least an upper second-class degree in a relevant discipline (computer or biomedical sciences, bioinformatics). Applicants with abilities and experience more specific to either one of these diverse sectors (i.e. mathematics/programming versus genomics/biomedicine) should be able to demonstrate an appetite and aptitude to acquire new skills.
You will meet the University of Southampton’s person specification for PhD candidates, which incorporates a full equality, diversity, and inclusivity policy.
The supervisory team
Your supervisory team of world-leading clinical scientists will be led by Sarah Ennis (Professor of Genomics) and Age Chapman (Professor of Computer Science). The studentship will be supported by a wide network encompassing the NIHR Southampton Biomedical Research Centre, Genomic Informatics and Data Science Research Groups and Clinical Informatics within University Hospital Southampton NHS Foundation Trust. You will be based in the Faculty of Medicine at the University of Southampton. If you wish to discuss this project further informally, please contact Professor Sarah Ennis ([Email Address Removed]).
How to apply
Complete the University of Southampton online application linked below. Please note:
- You must state project code DHS1 and the Data, Health and Society theme in the Personal Statement section of the online application.
- In the supervisor field on the application form please quote reference BRC/UoS/202223/842. You do not need to identify a supervisor.
- The online application references an Application Assessment Fee which is not required for this BRC project as it is a postgraduate research degree.
If you require further information, please contact Kay Mitchell, Senior Research Manager, at [Email Address Removed], or Karl Staples, Academic Career Development Lead, at [Email Address Removed]. Application enquiries can be directed to [Email Address Removed] for the Faculty of Medicine.
Closing date for applications: Friday 15th July 2022