NILab is a BBSRC-funded interdisciplinary programme that is at the forefront of artificial intelligence for biological sciences. NILab integrates AI technologies seamlessly into biological research, driving new discoveries and fostering effective collaboration between academia, industrial partners, and government bodies.

Our Vision:
To lead the research in AI-powered bioscience discovery by training doctoral researchers with unparalleled expertise in AI and biosciences.

NILab Structure

The NILab programme is structured to provide comprehensive training and development for PhD students through a combination of cohort training, personalised training, and research projects.

Year 1: Building a Strong Foundation

Cohort Training:
Introduction to Discovery AI: Foundational concepts and algorithms for AI-powered hypothesis generation, causality identification, and signature discovery within biosciences.

Research Methods and Group Project: Covers experimental design and computational methods, applied in a group project in AI for bioscience.

Entrepreneurship and Group Project: Key topics related to innovation, including IP and entrepreneurism, applied in a group project to develop and prototype a business idea.

Personalised Training:
Students design a personalised training plan with their theme lead, addressing specific knowledge gaps and thematic needs using modules from the QUB/UU MSc catalogue.

Summer Project:
A group project in AI for bioscience, culminating in a "conference paper".

Years 2-4: Research and Professional Development

PhD Research & Supervision:
Students work with a dedicated supervisory team comprising an AI expert and a bioscience expert, ensuring strong mentorship in both methodologies. Projects will delve into specific areas within AI for biosciences, utilising diverse data types, AI methodologies, and lab experimentation.

Personal Development and Transferable Skills (PD&TS):
Courses to enhance soft skills crucial for research careers, such as communication and project management.

Leadership Training:
To equip students with leadership skills for complex projects, team management, and effective communication.

Career Development:
Dedicated career guidance with workshops and advisors to explore diverse career paths, including non-research ones.

Industry Exposure:
Minimum 3-month placement with a bioscience or AI partner, providing practical experience aligning with student interests and research themes.

Networking & Public Engagement:
Opportunities to participate in conferences, presentations, science cafes, and outreach programmes to hone communication skills and raise awareness of AI-powered bioscience research.

Alumni Network:
A strong alumni network for professional development, collaboration, mentorship, and continued connection.

This structure ensures that NILab graduates are well-rounded researchers with a unique blend of AI and biosciences expertise, ready to drive transformative research and innovation across diverse sectors.

The Role of AI

NILab uses AI to harness its potential for transforming biological research, fostering interdisciplinary collaboration, and driving scientific and technological advancements in biosciences. NILab focuses on AI approaches for three types of discovery:

1. Causality Discovery – identifying biologically plausible causal mechanisms consistent with experimental observations.
2. Hypothesis Discovery – generating testable hypotheses based on knowledge about a biological system.
3. Signature Discovery – characterising biological phenomena based on experimental data.

Integrating these approaches into bioscience research will provide opportunity to automate data analysis, optimise experimental designs, and drive new innovations that lead to breakthroughs in understanding healthcare.

NILab Aims

The NILab programme aims to achieve the following end goals:

1. Develop a Skilled Workforce: Train 75 doctoral graduates with a unique combination of expertise in artificial intelligence (AI) and biological sciences, preparing them to drive innovation and solve complex challenges across health, agriculture, and environmental sectors.
2. Advance Bioscience Discovery: Develop and apply cutting-edge AI tools to accelerate discoveries in causality, hypothesis generation, and signature identification within biological systems.
3. Foster Collaboration and Leadership: Cultivate researchers who thrive in interdisciplinary teams, demonstrate leadership, and effectively communicate across domains to translate research into real-world impact.
4. Promote Responsible Innovation: Embed principles of Responsible Research and Innovation (RRI) and Equality, Diversity, and Inclusion (EDI) to ensure the programme supports a diverse and ethical research culture.
5. Drive Economic and Scientific Impact: Propel the UK's global competitiveness by contributing to advancements in bioscience research and fostering industry collaborations.

These goals align with NILab’s vision of leveraging AI to revolutionise our understanding of life and address pressing global challenges.