The Bloomsbury Colleges group was set up in 2004 and consists of five institutions: Birkbeck, London School of Hygiene & Tropical Medicine (LSHTM), the Royal Veterinary College (RVC), the School of Oriental and African Studies (SOAS), and the UCL Institute of Education (UCL–IOE). These studentships were set up to increase collaboration and interdisciplinary research opportunities across the colleges.
Applications are invited for three-year PhD studentships, to start in the academic year 2026-27. There are two studentships available at the London School of Hygiene & Tropical Medicine (where LSHTM is the lead institution): one studentship award per research project.
Funding
Each studentship will provide:
- tuition fees (at the LSHTM Home fee rate), and
- a student stipend (at the UKRI studentship rate, which is GBP 22,780.00 in 2025-26),
for the duration of the award.
Projects
The LSHTM-led studentship projects available for 2026-27 are:
- Devries and Weston: Using machine learning to understand coercive control
Supervisory team
- Principal Supervisor: Professor Karen Devries (London School of Hygiene and Tropical Medicine)
- Co-Supervisor: Dr David Weston (Birkbeck College)
Project description
Background
Globally, WHO estimates that one in three women will experience violence from an intimate partner in her lifetime. Alongside physical and sexual violence, emotional violence and coercive control are common features of these experiences. While the prevalence and types of acts of physical and sexual violence experienced by women are relatively well-characterised, emotional violence and coercive control remain less well understood.
The UK Crown Prosecution Service defines coercive control as “a pattern of behaviour that is used to make a person subordinate and/or dependent.” Current academic literature conceptualises three major ‘facets of the construct of coercive control in a relationship – 1) intentionality and motivation within the perpetrator to obtain control over the target; whether conscious or unconscious; 2) perception of the behavior as negative by the target, and 3) the ability of the perpetrator to make a credible threat as perceived by the target’2. These dynamics manifest in a large range of different behavioral acts, which make coercive control difficult to identify. Victims often remain in coercive and controlling relationships for years before being able to label them as abusive, and are often at risk for heightened abusive and controlling behaviours post-separation.
According to OfCom, in 2023, 67% of UK adults used WhatsApp as their main mode of text communication. Coercive, controlling and emotionally abusive communication between intimate partners is therefore highly likely to be captured in messages sent via WhatsApp and other digital platforms. Using modern machine learning methods, it is possible to characterise various features of textual communication as to overt qualities such as tone, including aggressive and sarcastic tones, and covert disruptive behaviour such as trolling. Indeed a pilot study funded by the home office has shown great promise for identifying coercive control 4 from textual communication albeit with a very small curated sample.
If machine learning analysis is able to identify fine-grained patterns of textual communication indicative of coercion and emotional abuse, there are numerous potential applications. A better characterisation of the communication patterns indicative of abuse would broaden academic understanding of these forms of abuse. These tools could be used by women themselves early on in relationships to understand whether communication can be classified as coercive or abusive. It could be offered to women by therapists, health practitioners, and legal practitioners to support diagnosis and appropriate provision of support.
Aims and objectives
The aim of this project is to explore whether machine learning can improve understanding and characterisation of communication patterns in coercive control against women. Specific objectives will be developed by the student. Provisional objectives are to: 1) describe features of text-based communication typical of coercive control; 2) compare these to features of non-coercive communication; 3) understand whether it is possible to develop a model that can classify women’s text communication as coercive or non-coercive.
Proposed methodology
The approach comprises three main phases:
- Data Collection and Curation
- Manual Labelling
- Model Development and Evaluation
Data Collection and Curation
In partnership with organisations who work with survivors of violence, we will invite survivors of violence who have experienced coercive control to refine project objectives in collaboration with the student and supervisors. A data collection strategy will be developed, and we envisage inviting about 50 women survivors to share anonymised versions of their WhatsApp histories. We will sample women without histories of coercive control, and aim to recruit approximately 50 women from each group. Text from these histories, stripped of all personally identifiable information but retaining timestamp metadata, will be the main data used in the analysis.
Manual Labelling
The raw text histories will be manually annotated to identify regions of coercive/non-coercive communication. These annotations will be validated by independent annotators and will serve as our ground-truth for subsequent experiments.
Model Development and Evaluation
to the student will investigate the extent to which regions of coercive control communication can be identified using Natural Language Processing (NLP) tools, beginning with replicating existing experiments in coercive control and further refine these approaches by using methods from adjacent problems such as identifying intimate partner violence from tweets. In particular, the student could explore whether linguistic or emotional frequency patterns serve as reliable features.
Ethical considerations
Devries has extensive experience working on violence against women and children, and will ensure that procedures are safe, ethical and respectful, and do not put participants at risk of further harm3. We will invite a survivor of violence to participate as a thesis advisor and will also invite survivors of violence to review our manual labelling framework developed during the PhD. The student will receivel training in safe approaches to involve survivors.
Significance
The work will be among the first application of machine learning to characterise and identify patterns of communication in coercive control, and is therefore likely to be highly significant for those working in the fields of violence and women’s health. If the approach is successful there are several practical applications possible.
The project is likely to be of substantial interest to violence survivors. One of the main issues that consistently emerges for survivors is wanting to better understand, and wanting more public awareness, of the coercive and controlling aspects of their abuse.
Timescale
The PhD will be organised over 3 years, starting from October 2026. Year 1 will involve the literature review. Year 2 will involve data collection and manual labelling, and exploratory data analysis. Year 3 will involve model development and evaluation. The PhD will be by publication.
Outcomes
The student will produce three academic papers: one literature review on the use of machine learning to characterise coercive control and emotional abuse; one descriptive paper which presents findings from the annotation and exploratory data analysis phase, and one based on evaluating NLP models for detecting coercive control.
Plans for dissemination
The student will widely disseminate the work, directly to survivors via partner organisations, at key academic conferences on violence (SVRI, ISPCAN) and applied computer science conferences, and via popular media.
Subject areas/keywords
Subject Area: behaviour, violence, computer science, epidemiology
Keywords: Natural Language Processing, machine learning, artificial intelligence, coercive control, violence
Key references
- https://www.cps.gov.uk/prosecution-guidance/controlling-or-coercive-beh…
- L. Kevin Hamberger, Sadie E. Larsen, Amy Lehrner. (2017) Coercive control in intimate partner violence. Aggression and Violent Behavior. Volume 37,Pages 1-11,https://doi.org/10.1016/j.avb.2017.08.003.
- WHO. (2001) Putting women first: Ethical and safety recommendations for research on domestic violence against women. WHO: Geneva
- Havard, T., Nnamokon, N., Magill, C., Demeocq, C., Procter, J., Harvey, D., & Bettinson, V. (2023). Using Artificial Intelligence to Identify Perpetrators of Technology Facilitated Coercive Control. Home Office: London
Further details about the project may be obtained from:
Principal Supervisor: Professor Karen Devries - [email protected]
Co-Supervisor: Dr David Weston - [email protected]
Deadline for applications
The deadline for applications is 16:00 (GMT) on 1 March 2026.
- Mostowy and Moores: Mapping the ultrastructural topology of septin cage entrapment
Supervisory team
Principal Supervisor: Professor Serge Mostowy (London School of Hygiene and Tropical Medicine)
Co-Supervisor: Professor Carolyn Moores (Birkbeck College)
Project description
Background
Shigella, a Gram-negative enteroinvasive bacterial pathogen, causes ~200 million cases of bacillary dysentery each year, and due to antibiotic resistance the World Health Organisation (WHO) has listed Shigella among its top pathogens requiring urgent action. Shigella is also recognised as an exceptional model pathogen to study key issues in cell biology and innate immunity.
Cell-autonomous immunity, the ability of a host cell to eliminate an invasive infectious agent, is a first line of host defence against bacterial pathogens. Recent studies of host-pathogen interactions have shown that cytoskeletal components are important for cell-autonomous immunity, yet underlying determinants are only beginning to emerge. We discovered that host cells prevent the actin-based motility of Shigella by entrapping bacteria targeted to autophagy inside ‘septin cages’, a mechanism of host defence that restricts bacterial dissemination. We showed that septins, a cytoskeletal component essential for many morphogenetic and signaling events, are recruited with autophagy proteins to cytosolic bacteria and counteract actin tail formation. Our results were first to highlight septins as structural determinants of host defence, and suggest that a comprehensive understanding of septin cage entrapment will have important consequences for understanding bacterial pathophysiology and its control.
Work which has led up to the project
We discovered that septins, which recognise and assemble on membranes presenting micron scale curvature, recognise membrane curvature of Shigella to arrest bacterial cell division, introducing bacterial cell shape as a danger signal triggering cell-autonomous immunity. Considering that septins have many roles in normal cell physiology, we used bottom-up cellular microbiology to create a cell-free platform for investigation of septin cage entrapment in isolation. We reconstituted the Shigella-septin cage in vitro using purified proteins, transforming our understanding of septin-bacteria interactions and its translational potential. It is next of great interest to understand how septins interact with the bacterial cell surface, and how septin cage entrapment is coordinated on the bacterial cell surface with other host factors (including actin, ubiquitin, autophagosomes) for Shigella infection control.
For this PhD project, we will combine cell-free reconstitution platforms (Prof. Mostowy) with innovative structural biology approaches (Prof. Moores) to study Shigella-septin cage entrapment. Building from results recently published, we will address fundamental gaps in knowledge through 2 synergistic research Aims.
Aim 1: Determine how septins interact with the Shigella cell surface
We discovered that septins recognise membrane curvature of Shigella to arrest bacterial cell division. From this, we hypothesise that host cells employ septins to sense intracellular bacteria based on biophysical cues as a new danger signal for cell-autonomous immunity. In combination with state-of-the-art microscopy techniques we will test this using our cell-free reconstitution system to reduce complexity and identify biophysical cues responsible for septin recruitment and cage assembly. Biophysical cues identified using Shigella may serve as universal danger signals presented by other intracellular bacterial pathogens (Gram-negative, Gram-positive) or damaged organelles (mitochondria, ER).
Considering that septin filament orientation at the yeast bud neck is linked to force generation in cell division, septin filament orientation may suggest a mechanical function for septins in inhibiting cell elongation or blocking septum constriction. To study this, we will perform cryo-EM. In-depth structural studies, using either single-particle reconstruction or cryo-ET according to the requirements of the sample, will determine how septin filaments self-assemble into higher-order oligomers upon bacterial surfaces in vitro. Together, investigation of biophysical cues promises identification of novel determinants modulating septin assembly and entrapment of Shigella into cages. Moreover, it can yield fundamental insights into septin biology and its links with membrane.
Aim 2: How do septins organise and functionalise the Shigella cell surface?
Septin filaments directly associate with membranes, where they act as diffusion barriers and serve as scaffolds to concentrate essential signaling molecules. We will use reductionist bottom-up cellular microbiology to study septin-mediated organization and function of the Shigella cell surface. In vitro reconstitution of the actin tail is a hallmark of cellular microbiology, and we will investigate the coordination of actin (tail) polymerization and septin (cage) assembly in vitro using bacterial surfaces and purified proteins. Studying how these processes are coordinated with each other, and also with other cellular processes (such as ubiquitination, autophagosome formation), will be necessary for a complete understanding of cell-autonomous immunity. We will use our cell-free platform, biochemistry and high-resolution microscopy techniques (super resolution, cryo-ET) to study coordination of host factors on the bacterial surface.
Perspectives
This project will provide the student with an opportunity to gain first-hand experience with cutting edge research on bacterial pathogens, cell free reconstitution systems, and advanced cryo-EM imaging techniques, significantly advancing our understanding of septin roles in health and disease. Through this project, they will receive extensive training in cell and molecular biology and imaging techniques, as well as invaluable experience working in the ISMB Electron Microscopy facility. Furthermore, both the Mostowy and Moores groups are engaged in several different London, UK, and international collaborations, exposing the PhD candidate to a wide range of interdisciplinary research and exciting opportunities for career advancement.
Subject areas/keywords
Subject Area: cell biology, structural biology, infection biology, microscopy, Shigella, septins, host defence
Keywords: cryo-electron microscopy, cytoskeleton, host-pathogen interactions
Key references
- Krokowski S, et al. (2018) Septins recognize and entrap dividing bacterial cells for delivery to lysosomes. Cell Host Microbe 24, 866-874. PMID: 30543779
- Manka SW, Moores CA (2018) Microtubule structure by cryo-EM: snapshots of dynamic instability. Essays in Biochem 62, 737. PMID: 30315096
- Lobato-Márquez D, et al. (2021) Mechanistic insight into bacterial entrapment by septin cage reconstitution. Nat Commun 12, 4511. PMID: 34301939
- Atherton J, et al. CA (2022) Visualising the cytoskeletal machinery in neuronal growth cones using cryo-electron tomography. J Cell Sci 135, jcs259234. PMID: 35383828
- Liu T, et al. (2025) Arp2/3-mediated bidirectional actin assembly by SPIN90 dimers. Nat Struct Mol Biol 32, 2262-2271. PMID: 40954369
Further details about the project may be obtained from:
- Principal Supervisor: Professor Serge Mostowy - [email protected]
- Co-Supervisor: Professor Carolyn Moores [email protected]
Deadline for applications
The deadline for applications is 16:00 (GMT) on 1 March 2026.
For details of studentships available at other Bloomsbury colleges but in collaboration with the London School of Hygiene & Tropical Medicine, please see the Bloomsbury Colleges website. Please apply directly to the lead institution only.
Eligibility
Applicants must meet minimum LSHTM entry requirements. Additional requirements may be necessary for each project. 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.
Successful international applicants may be eligible for an International Fee Waiver from LSHTM to cover the difference between Home and Overseas tuition fees. However, it should be noted that there is only one LSHTM fee waiver available on the Bloomsbury scheme in any academic year.
Please see our LSHTM statement regarding International Fee Waivers for further information.
Awardees may not use their Bloomsbury studentship stipend or personal funds to top up fees.
To apply
The application process has two steps. To be considered for the funding, applicants must meet all eligibility criteria and complete both steps outlined below by the scholarship deadline stated for the project they are applying for.
- Step 1
Submit an application for research degree study via the LSHTM application portal. Applicants should apply via the Faculty of Infectious & Tropical Diseases (ITD).- Students should submit a research proposal based on the advertisement for their project.
- Incomplete applications will not be considered for this studentship.
Step 2
Once you have submitted an application to study you should receive an automated email from the Scholarships Team ([email protected]) providing you with the link to our online scholarships application portal.
- This will provide you with a temporary password to use the first time you login (via e-vision), which you should then update.
- Please search for ‘Bloomsbury PhD Studentship’ if you wish to apply for this funding, and then answer the questions online to indicate your interest in one of the two funded PhD projects available. Once you are happy with your responses you can press submit and should receive a confirmation of receipt email at your contact email address.
- The scholarships portal will not be able to accept applications after the relevant project deadline (see below).
- The Scholarships team will be in touch with an outcome in due course.
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.
Applicants must meet the School’s minimum English language proficiency requirements if shortlisted for this funding by Monday 15 June 2026. Failure to do so may result in any scholarship offer being withdrawn and offered to a reserve candidate instead.
By submitting an application for this funding applicants agree to its Terms & Conditions.
Deadlines
The application deadline for Devries and Weston: Using machine learning to understand coercive control is 16:00 (GMT) on 1 March 2026.
The application deadline for Mostowy and Moores: Mapping the ultrastructural topology of septin cage entrapment is 16:00 (GMT) on 1 March 2026.
Please see the specific project information for further details.