Research Associate

Join us at the world-leading CRUK Cambridge Institute. We're a unique department of the University of Cambridge, core funded by Cancer Research UK's charitable activities, and we're eagerly searching for a
postdoctoral Research Associate
to join our Aliee Group.

In the Aliee lab, we aim to address fundamental questions in biomedicine through advancing machine learning. We develop models that represent and reason about complex biological systems, enabling predictions and interventions that can alter system behaviour in desired ways. For example, why do cells respond differently to stimuli? Why do patients vary in their responses to treatment? And what if the genome is altered - how would outcomes change?

Central to our work is the development of probabilistic generative models and counterfactual reasoning frameworks that uncover latent mechanisms and enable principled hypothesis testing. Our goal is to advance the theory of representation learning and causal inference in high-dimensional, structured data, ultimately uniting rigorous machine learning foundations with biological discovery.

To address these challenges, we work across a broad range of machine learning areas, including generative modelling (e.g., diffusion models, flow matching, self-supervised and autoregressive approaches), causal machine learning, dynamical systems modelling (e.g., neural ODEs and SDEs), identifiability and interpretability, large language and sequence models, and multimodal data integration.

For further information about the research group, including their most recent publications, please visit our website at

We offer positions in both foundational and applied research.

Foundational research
focuses on developing advanced AI models - such as identifiable generative models, causal models, agent-based systems, and sequence models - tailored to address complex biological problems. A key emphasis is on integrating prior knowledge from text and other modalities with biological data and experimental findings to generate hypotheses and drive discovery.

Applied research
involves extending recent advances in machine learning to biological datasets, with particular emphasis on patient stratification and uncovering individual differences that inform personalised treatments. We are also deeply interested in understanding how cells make decisions and establish their identities - questions we investigate by advancing causal models to uncover the interactions driving these processes.

We require a collaborative Research Associate to join the team to:

• Work with the group to develop research objectives and proposals.
• Conduct individual and collaborative research projects, writing up research work for presentation and publication.
• Continually update knowledge and understanding in field or specialism.
• Translate knowledge of advances in the subject areas into research activity.
• Manage own research and administrative activities, with guidance if required.
• Assist in the preparation of proposals and applications to external bodies, e.g. for funding and contractual purposes.
• Communicate material of a specialist or highly technical nature.
• Assist in the day-to-day supervision of student projects.
• Assist in the development of student research skills where appropriate.
• Plan and deliver seminars relating to research area.
• Build internal and external contacts and participate in networks for the exchange of information and to form relationships for future collaboration.
• Plan the use of research resources, laboratories and workshops as appropriate.
• Plan and manage own research activity in collaboration with others
• Contribute to planning of joint research projects led by Dr Aliee.

Click the 'Apply' button below to register an account with our recruitment system (if you have not already) and apply online.

Please ensure that you upload a covering letter and CV in the Upload section of the online application. The covering letter should outline why you wish to be considered for the post, and your experience to date.

Fixed-term: The funds for this post are available for 2 years in the first instance, with the possibility of extension in the future.

If you have any queries regarding the application process, please contact: mailbox-

Please quote reference SW47649 on your application and in any correspondence about this vacancy.

The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.

The University has a responsibility to ensure that all employees are eligible to live and work in the UK.

Apply online