Support Research Delivery and Operations across the Programme

We’ll carve out a specific set of partners and tasks (aligned with your PhD topic) whom you will be the primary point of contact for, spanning operational and technical needs (as summarised below). Your job will be to make sure those elements of the grant-funded projects we’re collaborating on with our partners happen as planned.

• Support the AI for Health team’s research agenda: contribute technical input as the team and its partners design, run, and analyse evaluation studies, including developing and testing simulated users/patients and LLM-judges and running evaluations of AI models and products.
• Work with the Deputy Director of Operations and Finance and their team on the operational, administrative, and project management components of research delivery, including ethics and governance submissions, partner reporting, and workplan tracking.
• Develop Your Research Skills

Complete a fully funded PhD at University College London as the core vehicle for developing your research skills. Under the guidance of your supervisors, conceive, design, and carry out the studies that make up your thesis, which will address how human expertise and local data can most effectively and efficiently be used to deliver accurate and localised evaluation of AI performance across different languages and contexts. Topics could include:

• Analysing what clinicians and lived experience experts in different countries consider to be helpful and harmful AI behaviour: what is shared between contexts, what is local to individual settings, how much different experts agree/disagree, and how plurality of opinion can be represented in our evaluations.
• Developing and adapting automated evaluation methods to reflect how people in each setting talk about their mental health and seek support from AI, including in local languages and where people mix languages.
• Studying how to make the most of scarce expert time and local data: which ways of collecting expert feedback and data improve our evaluation tools most efficiently, and how much ongoing human input we need to stay reliable.
• Contribute to studies led by other members of the AI for Health team, and to the development of the team’s wider research agenda, whilst building your own methodological and technical skills over the course of the post, with the support of your supervisors.

This is a full-time post based in London, combining research delivery at PATH with registration for a PhD at University College London, fully funded for three years. You’ll report to PATH’s Deputy Director for AI for Health, and your PhD will be jointly supervised by leadership at PATH and UCL. The role includes occasional international travel to partner sites (around 5-10% of time).

Required Skills and Experience:

• MSc or BSc in data science, psychology, cognitive science, statistics, computer science, human–computer interaction, computational linguistics, epidemiology, or a related quantitative discipline.
• At least two years’ research experience beyond your degree, in academia, industry, or a research organisation.
• Strong grounding in experimental design and measurement—reliability, validity, inter-rater agreement, calibration—and in statistical modelling (e.g., mixed-effects or Bayesian models).
• Hands-on experience working with large language models and/or large text datasets, and familiarity with relevant programming languages.
• Ability to work well with expert panels and partners from diverse backgrounds, and to handle sensitive mental health content with care.
• Excellent written English, with evidence of scientific writing (thesis, preprint, or publication).

Preferred Qualifications

• Experience in mental health research, digital health, or human–AI interaction.
• Experience with cross-cultural or multilingual measurement, or with natural language processing beyond English.
• Experience working with collaborators in low- and middle-income countries, ideally in sub-Saharan Africa.
• Experience evaluating, prompting, or fine-tuning large language models.
• Familiarity with lived-experience involvement in research.

We know great candidates won’t always meet every listed qualification. Research shows that some groups, on average, are more likely to self-select out if they feel they don’t meet all requirements. If you’re excited about the role and think you’d be a good fit, we encourage you to apply.

To be selected, you must have legal authorization to work in the United Kingdom.