Agentic AI for Integrative Multi-Omics Research in Cancer The University of Manchester in United Kingdom

This PhD opportunity at The University of Manchester invites applications for a cutting-edge research project at the intersection of artificial intelligence and cancer biology. The project, based in the Department of Computer Science, aims to develop and apply novel Agentic AI frameworks to tackle the integration and interpretation of multi-omics data in cancer research. Cancer's complexity arises from genomic, transcriptomic, proteomic, and metabolomic alterations, and while high-throughput technologies have enabled comprehensive molecular profiling, a holistic understanding of these layers remains a major challenge. Traditional computational approaches often fall short in handling the scale and heterogeneity of such data, limiting insights into tumour progression and therapeutic resistance.

The successful PhD candidate will move beyond conventional machine learning, building and deploying sophisticated AI agents capable of autonomous exploration of vast multi-omics datasets. These agents will formulate and test hypotheses, collaborate to construct coherent models of cancer biology, and emulate aspects of the scientific discovery process. The ultimate goal is to identify novel diagnostic biomarkers, pinpoint key molecular pathways for therapeutic intervention, and provide a systems-level understanding of cancer mechanisms.

Project methodology includes designing multi-agent AI architectures using deep learning, reinforcement learning, and large language models (LLMs). Each agent will specialize in a particular data type (e.g., genomics, proteomics) and integrate knowledge from public databases such as TCGA, Gene Ontology, and KEGG pathways. A collaborative reasoning framework will enable agents to communicate findings, debate evidence, and generate testable hypotheses. Hypotheses will be validated through bioinformatics pipelines and, where possible, experimental collaboration with biomedical partners. Emphasis is placed on interpretable models to ensure transparency and mechanistic plausibility.

Applicants should have a strong background in computer science, bioinformatics, computational biology, or related fields, with proficiency in Python and machine learning libraries (PyTorch, TensorFlow, Scikit-learn). Experience with large language models, Agentic AI, and foundational AI models is highly desirable, as is knowledge of molecular biology, genomics, or cancer biology. Analytical and problem-solving skills, creativity, and independence are essential. English language certification may be required for non-native speakers.

This is a 3.5-year PhD position, with excellent candidates nominated for competence-based funding. The University of Manchester offers a range of scholarships, studentships, and awards for both UK and overseas postgraduate researchers. The start date is October 2026, and early application is recommended as the advert may be removed once filled. The university is committed to equality, diversity, and inclusion, welcoming applicants from all backgrounds and supporting flexible study arrangements.

To apply, contact Dr. Jingyuan Sun ([email protected]) with your academic background and motivation. Applications are submitted online via the university portal, specifying the project title and supervisor. Required documents include transcripts, CV, referee contacts, and English language certificate if applicable. For questions, email [email protected].