About NILAB
NILab is a BBSRC-funded interdisciplinary doctoral research programme that is at the forefront of integrating artificial intelligence (AI) with biological sciences. It is a collaboration between Queen’s University Belfast and Ulster University. It brings together academia, industry partners, and government bodies on a mission to integrate AI technologies seamlessly into bioscience research to accelerate discovery and foster innovation across health, agriculture, and environmental sectors.
Vision and Mission
Our vision is to accelerate scientific discovery in biological sciences through AI to advance our understanding of life sciences, improve human and animal health and address pressing global challenges of our time. Our mission is to conduct and lead AI-powered bioscience research by training 60 doctoral researchers with cutting-edge interdisciplinary expertise in AI and biology.
The Role of AI
AI plays a central role in NILab by transforming the way bioscience discoveries are made. NILab focuses on three core discovery areas where AI has the potential to accelerate progress:
- Causality Discovery – identifying biologically plausible causal mechanisms based on experimental observations.
- Hypothesis Discovery – generating testable hypotheses from existing biological knowledge and experimental data.
- Signature Discovery – characterising biological phenomena by uncovering patterns in complex experimental data.
By integrating these AI approaches into bioscience research, NILab aims to enable automation of data analysis, optimisation of experimental design, and acceleration of scientific discoveries in life sciences and healthcare.
Through this, NILab will not only advance bioscience research but also promote interdisciplinary collaboration and technological innovation in biological sciences.
NILab Objectives
- Develop a Skilled Workforce: Train 60 doctoral researchers with a unique blend of AI and bioscience expertise, equipped to tackle complex challenges across sectors.
- Advance Bioscience Discovery: Develop and apply state-of-the-art AI tools to support causal discovery, hypothesis generation, and signature identification within biological systems.
- Foster Collaboration and Leadership: Cultivate researchers who thrive in interdisciplinary environments, demonstrate leadership, effectively communicate across domains, and translate research into real-world impact.
- Promote Responsible Innovation: Embed principles of Responsible Research and Innovation (RRI) and Equality, Diversity, and Inclusion (EDI) to ensure an ethical and inclusive research culture.
- Drive Economic and Scientific Impact: Enhance the UK's global competitiveness by advancing bioscience research and innovation, and fostering academia-industry collaboration.
NILab Programme
The NILAB Programme is a four-year doctoral research programme designed to develop the next generation of research leaders working at the interface of AI and the biological sciences, by equipping doctoral students with the knowledge, skills, and experience required to deliver impactful research and to pursue diverse careers across academia, industry, and beyond. Through collaboration with a variety of Stakeholders, such as Industry, Government and NGOs, the programme will provide student experience on research with impact.
The programme is centred on high-quality PhD research, supported by a multidisciplinary supervisory team bringing together expertise from both AI and biological sciences. The programme is enhanced by a range of training activities delivered throughout the programme. These include bespoke modules such as Discovery AI, which introduces foundational concepts related to AI-driven discovery research, as well as collaborative group projects and seminar series, fostering cross-disciplinary learning and critical engagement with emerging topics. The programme is further enhanced by professional development training designed to build essential transferable skills, including scientific communication, academic writing, research ethics and integrity, project and time management, leadership, and teamwork.