NILab is a BBSRC-funded interdisciplinary training 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 and train 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, personalized 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 tailored to bioscience or AI themes.

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.

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

Individual Mini Project:
A training activity co-designed by the student and their supervisory team to prepare for the summer project and PhD.

Summer Project:
An individual project building on the mini-project, culminating in a "conference paper" and a detailed proposal for future PhD research.

Years 2-4: Research and Professional Development

PhD Research & Supervision:
Students work with a dedicated supervisory team comprising an AI expert and a biosciences expert, ensuring strong mentorship in both methodologies. Projects will delve into specific areas within discovery AI for biosciences, utilizing 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:
A bespoke programme 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 revolutionize biological sciences by leveraging its transformative potential to accelerate discovery processes. NILab will focus 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.

NILab uses AI to revolutionize biological sciences by leveraging its transformative potential to accelerate innovation. Integrating these approaches into bioscience research will provide opportunity to automate data analysis, optimize experimental designs, and drive new innovations that lead to breakthroughs in understanding healthcare.

Overall, NILab uses AI to harness its potential for transforming biological research, fostering interdisciplinary collaboration, and driving scientific and technological advancements in biosciences.

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 revolutionize our understanding of life and address pressing global challenges.