Correlates of Immunity – Artificial Intelligence (CoI-AI), DPhil Programme

About the CoI-AI Programme

The Correlates of Immunity – Artificial Intelligence (CoI-AI)  programme is based at the Oxford Vaccine Group, University of Oxford, and supported by the Ellison Institute of Technology, and co-led by Professor Sir Andrew Pollard and Professor Daniela Ferreira.

The programme aims to transform how vaccines are designed by combining experimental medicine, cutting-edge immunology and artificial intelligence to better understand how the human immune system protects against infection. By identifying the immune responses that correlate with protection, CoI-AI seeks to accelerate the development of next-generation vaccines and improve the prevention of bacterial diseases that continue to cause substantial global morbidity, mortality and antimicrobial resistance.

The programme focuses on bacterial pathogens for which effective vaccines are lacking or where current vaccine approaches remain inadequate, including Staphylococcus aureus (a major cause of bloodstream, skin and soft-tissue, and bone and joint infections), Neisseria gonorrhoeae (the causative agent of gonorrhoea and a growing antimicrobial resistance threat), Escherichia coli (the leading cause of urinary tract infections and an important cause of sepsis), Group A Streptococcus (a major cause of pharyngitis and skin infections, as well as severe invasive disease), and Streptococcus pneumoniae (a leading cause of pneumonia, meningitis and bloodstream infections, particularly in young children and older adults). Across these pathogens, the programme aims to define the mechanisms of protective immunity and translate these insights into new approaches to vaccine development.

To achieve this, we are establishing innovative controlled human infection models (CHIMs) and prospective clinical cohort studies that provide opportunities to investigate host–pathogen interactions and immune responses to infection and vaccination, identify biomarkers and candidate antigens, and apply artificial intelligence to complex clinical and immunological datasets.

The CoI-AI research portfolio includes studies at different stages of development and delivery, including:

• Understanding immune correlates of protection against nasal colonisation with Staphylococcus aureus using a Controlled Human Infection Model (ReSET Study).
• Investigating host immune responses during experimental Staphylococcus aureus skin infection (SAFESkin Study).
• Defining immune responses to Neisseria gonorrhoeae using a Controlled Human Infection Model (ChaNGE Study).
• Developing an Escherichia coli Controlled Human Infection Model to investigate immunity to urinary tract infection.
• Clinical cohort studies of bacterial infections to identify immune correlates of protection and support AI-enabled biomarker discovery.

Why join the CoI-AI DPhil Programme?

As a CoI-AI DPhil student, you will become part of a multidisciplinary team of clinicians, scientists, microbiologists, immunologists and computational researchers working together to address globally important challenges in infectious diseases.

DPhil students will join a collaborative research environment spanning experimental medicine, laboratory science and computational biology. Depending on your project, you may have opportunities to:

• contribute to the design, delivery and analysis of innovative clinical studies, including controlled human infection models and patient cohort studies;
• work with unique clinical samples and high-dimensional immunological datasets generated through the CoI-AI programme;
• gain training in experimental medicine, clinical trials, immunology, microbiology, systems biology and artificial intelligence;
• collaborate with researchers across the University of Oxford, the Ellison Institute of Technology and leading international academic and industry partners;
• present your work at national and international scientific meetings; and
• develop the scientific, clinical and leadership skills needed for a career in academia, clinical research or the biotechnology and pharmaceutical sectors.

Students will receive comprehensive supervision and mentorship from internationally recognised investigators and will become part of a collaborative research environment committed to advancing next-generation vaccines, diagnostics and therapeutics.

Available Projects

Candidates are invited to discuss potential DPhil projects within the CoI-AI Programme with the relevant project leads before submitting an application. DPhil projects are embedded within an active CoI-AI research programme and offers opportunities to contribute to the design, delivery and analysis of clinical studies, alongside laboratory and computational research where appropriate. Projects span clinical research, microbiology, immunology and antigen discovery and can be tailored to the successful applicant's background, interests and career aspirations in discussion with the supervisory team.

For further information about the research areas and potential DPhil projects, prospective applicants are encouraged to contact the relevant project lead below:

• Staphylococcus aureus human challenge studies: Dr Rob Shaw
• Neisseria gonorrhoea human challenge studies:  Associate Professor Susanne Hodgson
• E. coli human challenge studies:   Dr Paola Cicconi
• Clinical cohorts of bacterial infections: Professor Susie Dunachie
• Antigen Discovery and Vaccine Development: Dr Young Kim

Eligibility

Applications are welcomed from outstanding graduates and registered healthcare professionals with backgrounds in medicine, microbiology, immunology, infectious diseases, biomedical sciences, bioinformatics, computational biology or related disciplines.

Applicants should have a strong academic record and a demonstrated interest in translational infectious disease research.

How to Apply

Applicants should:

• identify a project of interest;
• contact the project lead(s) to discuss the project before applying;
• submit their application here.

Shortlisted applicants will be invited to interview.

Interviews will be conducted by a panel including Professor Daniela Ferreira, Professor Sir Andrew Pollard, project lead(s), and additional members of the Department.