Does AI Help Biologists to Record Their Science? Open Research from Electronic Lab Notebooks University of Edinburgh in United Kingdom

This PhD project at the University of Edinburgh investigates whether electronic lab notebooks (ELNs) truly enhance the recording and sharing of scientific data among biologists, leveraging current machine learning and AI methods. As research teams transition from paper to digital records, the assumption is that ELNs improve data documentation and facilitate open data dissemination. However, empirical evidence for these benefits is limited, and this project aims to rigorously assess the impact of ELNs on research records and data sharing practices.

Supervised by Professor Andrew Millar (BioRDM team, Biology) and Professor Malcolm MacLeod (CAMARADES group, Medicine), with input from ResearchSpace (developers of the RSpace ELN), the successful candidate will collaborate with meta-researchers and software developers. The project will analyze ELN entries and open data from multiple research groups, develop and test an AI-based 'suggester' tool to improve data descriptions (such as adding ontology terms), and evaluate how ELNs influence FAIR and open data sharing compared to current practices in Edinburgh biosciences.

The student will be based in the C.H. Waddington building, at the Centre for Engineering Biology, and will benefit from the University’s strong training in AI and data stewardship. The research is highly interdisciplinary, spanning bioinformatics, biotechnology, cell and developmental biology, human and molecular genetics, neuroscience, and plant biology. The project is designed to produce widely relevant results for ELN users and contribute to the advancement of open research practices.

Applicants should hold or expect to obtain a first class or upper-second class Bachelor’s degree (or equivalent) in Biology or Biomedicine, with some data science training or research experience. The position is open to International/EU candidates, with funding options including the Darwin Trust-funded PhD studentship, which covers tuition fees and provides an annual stipend of £22,700 for the 2025-26 academic year.

To apply, candidates should send an initial application (CV and cover letter) by email to Prof. Andrew Millar, outlining their relevant skills and experience. Formal applications must be submitted via the University of Edinburgh’s admissions portal (EUCLID), specifying the project title, supervisor, and anticipated funding source. Applicants seeking Darwin Trust funding must also submit a separate funding application to the Trust. The application deadline is January 7, 2026, with a planned start date of October 1, 2026.

For further details, see the project page and references provided, including recent studies on ELN implementation and open data practices. This is an excellent opportunity for candidates interested in the intersection of biology, data science, and open research to develop expertise and contribute to the future of scientific data management.