2024-25 Grogan-Mohr PhD in Wolbachia Research

We are pleased to invite applications for the Grogan-Mohr PhD in Wolbachia Research in the field of vector-borne disease, epidemiology and modelling. The London School of Hygiene and Tropical Medicine (LSHTM) has been gifted funding by Mrs Sarah Mohr & Dr Phillip Mohr to support a PhD studentship aimed at progressing the research in Wolbachia.

One PhD studentship is available starting in October 2024 for a duration of four years. The award will cover a tax-free stipend, tuition fees, a high specification laptop computer, training courses and travel to international conferences. This studentship is open to “home” and international candidates.

The successful candidate will use computational models to develop the global health investment case for developing a Wolbachia replacement solution for malaria. Over the course of this PhD you will develop computational and statistical expertise and learn how to combine diverse datasets from the fields of ecology, epidemiology and economics to support the development of new products that could save hundreds of thousands of lives a year.


The studentship will provide:

  • Tuition fees (at the LSHTM Home or Overseas fee rate), and
  • Student Stipend (at the UKRI studentship rate, which is GBP 20,622.00 in 2023-24)
  • Research Training and Support Grant to go towards consumables and training for the duration of the award.

Who you will be working with

While a PhD primarily requires you to work independently and take ownership of your own work, you will also have access to a broad range of expertise at different levels. Your primary supervisor will be Dr. Oliver Brady who brings expertise in dengue epidemiology and secondary supervisor Dr. Thomas Walker at the University of Warwick who brings a range of experience and specialist expertise on Wolbachia and laboratory experimental studies.

Day-to-day you will work with the Dengue Mapping and Modelling Group (DMMG). We are a medium sized (6-9 people) collaborative and friendly group with a range of technical and applied expertise with approachable colleagues across a range of career stages. The DMMG group and this studentship are “remote friendly” with a required minimum in person attendance in London of 8 days a month with a general high degree of flexibility on when and where you work.

You will also be part of the (~ 100 people) Centre for the Mathematical Modelling of Infectious Diseases (CMMID) and one of the largest infectious disease departments in Europe (Infectious Disease Epidemiology), allowing you to develop and specialise your modelling expertise and apply such skills to a broad range of applied public health issues.

By the end of this PhD you will have:

  • An ability to formulate, parameterise and fit computational models to a variety of laboratory and field data sources using state of the art techniques.
  • An in depth understanding of the criteria different global health actors use to decide whether to invest in new interventions
  • Experience working with academics, funders and ministries of health

Past group members developing similar skillsets have gone on to secure highly competitive jobs in Academia, government health departments, health-focused non-governmental organisations, research funders and industry.


While this studentship will expose the candidate to multidisciplinary research skills across the fields of modelling, epidemiology and health economics, the core skills needed on a day-to-day basis for this studentship are computational and technical with high attention to detail being critical. You should have quantitative approach to problem solving and a solid understanding of statistical concepts. You will be comfortable taking ownership of your work and problem solving independently, but also know when to collaborate to achieve objectives most efficiently.


  • Applicants must hold, or expect to obtain before the start of the PhD, a relevant (typically quantitative science-based) MSc awarded with good grades, or have a combination of relevant qualifications and experience which demonstrates equivalent ability and attainment.
  • An ability to effectively and independently solve problems from small technical issues (e.g. coding errors) to broader research directions.
  • Experience developing statistical or dynamic models, ideally in the health field.


  • An understanding of malaria epidemiology
  • Computer coding expertise, preferably in R
  • Experience with geographical information systems (GIS) and geostatistical modelling
  • Experience working with ministries of health, global health agencies or corporations that develop new interventions and an understanding of the decision making process of developing and adopting new interventions
  • An understanding of health economics

Applicants must meet minimum LSHTM entry requirements. Please see the specific project information for further details.

These studentships are open to applicants assessed as both ‘Home’ and ‘Overseas’ fee status. For further information about Fee Status Assessments please see the School’s policy and procedure document.

Supervisory team

Principal Supervisor: Oliver Brady

Co-Supervisor: Tom Walker (University of Warwick)

Project description

Malaria kills over 600,000 people – mostly children – every year. Despite widespread use of bed nets, insecticides, drugs and now vaccines, progress has stalled and new interventions are needed to achieve elimination. When certain species of Wolbachia, an intracellular bacterium, are inserted into mosquito cells they can disrupt the ability of the mosquito to transmit pathogens. Replacement of mosquito populations with Wolbachia infected mosquitoes has led to substantial reductions in the incidence of dengue, offering hope that Wolbachia replacement may be useful intervention for other vector-borne diseases.

Mathematical models can be used to support the development of new interventions by identifying where in the world they would be used, predicting what effects they will have when combined with other interventions in real-world settings and by estimating cost effectiveness over the long term. In this project the candidate will:

  1. develop a population-level Anopheles mosquito model based on laboratory experiment data from the most promising Wolbachia species to study the dynamics ofspread at different temperatures
  2. use global maps of temperature, mosquito species, malaria prevalence and intervention use to map where Wolbachia can address unmet health needs
  3. develop transmission models to explore how and when Wolbachia can be combined with other malaria control interventions
  4. assess the potential cost effectiveness of a Wolbachia replacement intervention for malaria, including comparisons with other interventions.

Combined, these analyses will shape key decision making steps for product developers, countries and world health bodies in the development of a Wolbachia replacement intervention for malaria.

Subject areas/keywords

Mathematical modelling; infectious disease; epidemiology; malaria; mosquito

Key references

To apply

Information about the MPhil/PhD programme structure at LSHTM, as well as application guidance can be found on the School’s Research Degrees and Doctoral College pages.

To apply for this studentship, applicants should submit an application for research degree study via the LSHTM application portal. The applicant should apply via the Faculty of the Primary Supervisor (EPH – Faculty of Epidemiology & Population Health) and must indicate that they are applying for ‘Grogan-Mohr Malaria Control Research Studentship’ in the Funding Section on the admissions application.

Students should submit a research proposal based on the advertisement for this project.

Please use the Personal Statement part of your application to study at LSHTM, to describe how your past experience provides you with the essential and desirable skills listed in the advert.

Incomplete applications will not be considered for this studentship.

Applications for this project will only be reviewed and processed after the deadline. All applications that are submitted before the deadline will be considered equally, regardless of submission date.   

If invited for interview, there will be a short experimental design problem, shared in advance, that will be used to assess some of the technical aspects of your experimental approach to problems of relevance to this project.

By submitting an application for this funding applicants agree to its Terms & Conditions.


The application deadline is 23:59 (GMT) on 19 May 2024.