Enabling Next-generation AI for a Bioscience Led Economy

A four-year doctoral programme uniting world-leading AI research and bioscience innovation across Oxford, Birmingham, Aberystwyth and the Francis Crick Institute.

ENAIBLE leads to a DPhil at Oxford or a PhD at Birmingham or Aberystwyth. We are now OPEN for applications to commence study in Autumn 2026.

Our Purpose

ENAIBLE prepares researchers for an AI-driven era of biology ("Biology 2.0"), in which computational systems are active partners in scientific discovery.

Across the UK, bioscience is one of the most strategically important sectors of the economy. Advances in AI are transforming how discovery happens, from hypothesis generation to modelling, experimentation and translation. 

ENAIBLE tackles a critical UK skills gap: developing advanced AI and data-science capacity for the £100 billion bioscience sector. 

The UK urgently needs researchers fluent in both bioscience and the mathematical and computational foundations of next-generation AI, capable of applying these technologies responsibly to the complex, data-rich biological systems that underpin our health, food, and environment.

The programme equips you with the technical depth, biological understanding and ethical awareness required to lead in AI-first bioscience. Supported by the Biotechnology and Biological Sciences Research Council (BBSRC), part of UK Research and Innovation (UKRI), we are building national capability in AI-driven, data-intensive bioscience by investing in your doctoral training.

Oxford has long been a place where disciplines meet and new fields begin. ENAIBLE builds on that tradition, bringing together artificial intelligence, mathematics and the life sciences to train a generation of researchers who will shape the future of biology.

As a BBSRC-funded programme, DPhil projects must align with BBSRC remit and priority areas within the biosciences.

Why ENAIBLE? 

A partnership of exceptional institutions

ENAIBLE is led by the University of Oxford in partnership with the University of Birmingham, Aberystwyth University (IBERS), and the Francis Crick Institute — institutions recognised internationally for excellence in AI, computational science, biology and translational research.

You benefit from:

• Oxford’s globally recognised strength in AI, mathematics, computer science and biomedical research.
• Birmingham’s expertise in AI and data science, healthy ageing and translational medicine.
• IBERS’ internationally leading research in crop science, environmental biology and sustainable systems.
• The Francis Crick Institute’s state-of-the-art biomedical discovery environment and large-scale data generation platforms. The Crick contributes research supervision and facilities; degrees are awarded by the partner universities.

Together, these institutions form the academic core of ENAIBLE.

Industrial and International Engagement

Beyond its academic partners, ENAIBLE draws on industry partnerships. 

ENAIBLE connects students to a broader international and data-driven research landscape. This includes engagement with initiatives such as AITHYRA — a major European institute focused on AI-first approaches in the biological sciences — and community data resources such as those supported by the Chan Zuckerberg Initiative (CZI). These relationships expand the range of datasets, infrastructures and translational contexts available to you, strengthening the programme’s real-world relevance while preserving academic independence.

Industry partnerships provide:

• Opportunities for CASE studentships and industry-linked DPhil projects.
• Access to real-world datasets and translational research challenges.
• Structured placements and mentoring from industry professionals.

You gain exposure to applied research environments, while partners benefit from cutting-edge methodological advances and doctoral-level insight. 

The ENAIBLE Difference

Our layered model - academic excellence at the core, supported by industrial and international engagement - creates an environment that no single institution could provide alone.

• A distinctive four-year structure: one year of intensive, cohort-based interdisciplinary training followed by three years of doctoral research.
• Small cohort. Large ecosystem.
• Recruitment of six fully funded DPhil students per year (subject to change), ensuring a focused, high-calibre ENAIBLE group embedded within a wider interdisciplinary community.
• Training in next-generation AI methods, data-driven modelling, bioscience experimentation and bioethics.
• Two interdisciplinary rotation projects in Year 1 to shape and refine your doctoral direction.
• A minimum three-month professional placement with a partner organisation.
• Co-supervision combining computational and experimental expertise across institutions.

Is ENAIBLE the Right Programme for Me?

A doctoral degree is a major commitment — intellectually, professionally and financially. You should expect depth, challenge and long-term return. ENAIBLE is designed for you if you want more than a conventional PhD.

You may be a strong fit if you:

• Want to work at the frontier where AI and biology genuinely reshape how discovery happens.
• Are excited by rigorous mathematics, machine learning and computation, and equally motivated by real biological or biomedical problems.
• Prefer structured cohort-based training in your first year rather than immediate isolation within a single research group.
• Value exposure to industry, translation and real-world datasets alongside academic depth.

• Intend to lead, in academia, biotechnology, AI, health, agriculture or data-intensive research environments.

   

Why ENAIBLE rather than another programme?

• Integrated training before specialisation. You build a serious technical foundation across AI, modelling, experimentation and bioethics before committing to a DPhil project.
• Selectivity and scale. With six funded places per year, you join a focused, high-calibre cohort with direct access to programme leadership.
• Cross-institutional supervision. You are not confined to a single department; you benefit from expertise spanning Oxford, Birmingham, IBERS and the Crick Institute.
• Structured industry engagement. Placements and industry-linked opportunities are built into the programme design, not left to chance.
• Long-term positioning. You graduate with fluency in both advanced AI methodologies and complex biological systems, a combination increasingly rare and highly sought after.

If you are seeking a purely single-discipline doctorate, ENAIBLE may not be the right fit. If you want to operate confidently across computational and experimental domains, and to help define how AI reshapes the biosciences, this programme is designed for you.

How Will ENAIBLE Advance My Career?

Oxford’s doctoral training has produced leaders across academia, industry and the public sector. ENAIBLE builds on that legacy while extending it into AI-driven bioscience.

By the end of the programme, you will be equipped to:

• Lead interdisciplinary research programmes in academia.
• Drive innovation in biotechnology, pharma, agri-tech and data-intensive industries.
• Translate AI-enabled discoveries into clinical, agricultural and environmental impact.
• Shape ethical and responsible use of AI in science and society.

Just as importantly, you build long-term intellectual capital through the network around you.

During Year 1, you are embedded within a DTC community of more than 90 doctoral researchers per annum across multiple interdisciplinary streams. Shared teaching, joint projects and informal exchange mean your network quickly extends beyond ENAIBLE itself.

Over time, these relationships become part of your professional infrastructure: collaborators in future grants, co-founders in new ventures, policy advisers, technical leads and research partners across sectors.

Through structured mentoring, professional development, placements and access to the DTC alumni network, ENAIBLE prepares you not just to complete a doctorate, but to operate within (and help shape) an influential interdisciplinary community long after graduation.

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