Principal Investigator of Biomedical Data Sciences

We are seeking an experienced Data Scientist with a focus on drug discovery to develop their own research interests as part of a broader effort in Computational Drug Discovery within the Drug Discovery Unit (DDU) at the University of Dundee. This is an exciting position with a goal to develop and apply novel data science algorithms to live drug discovery programmes in infectious diseases (affecting Low- and Middle-Income Countries) and innovative targets in a range of human diseases. There are significant opportunities to collaborate with other scientists with the Schools of Life Sciences and Medicine at the University of Dundee, who have large datasets of medically and biologically relevant data.

This recruitment is part of the School of Life Sciences’ wider research strategy where we are looking to recruit up to 45 research active Group Leaders/Principal Investigators over the next 5-year period across all molecular life sciences research. It is therefore an exciting opportunity to contribute to our future direction.

What this post offers

This post offers the successful applicant an opportunity to develop and deliver on the Data Science strategy for the DDU to facilitate drug discovery programmes and create novel insight on the data rich environment that exists there. The role will partner with data management, computational biology, computational chemistry, bioinformatics, proteomics and research IT to develop and apply state of the art algorithms for knowledge creation and impact. The unit has been well funded and has a significant repository of well annotated data suitable for AI & ML interrogation and validation. The post is available immediately and will report to the Head of the Computational Drug Discovery. The salary is dependent on experience.

Required Attributes
  • Application of data science approaches to produce actionable insights for Drug Discovery. Experience with a broad range of techniques such as AIML (LLMs), knowledge graph creation/analysis, disease modelling and natural language processing (NLP)
  • A degree and PhD in a degree related to Data Science, Maths, Systems Biology, Bioinformatics, NLP and Cheminformatics
  • Machine learning and/or statistical modelling techniques. Strong coding ability in Python. Candidates should be familiar with some of the packages that support bioinformatics, chemoinformatics, data science and/or machine learning activities.
  • A strong publication, translation or patent track record.
  • Ability to develop and lead multidisciplinary teams of scientists.
  • Initiative and willingness to work flexibly to meet milestones and deadlines.
  • Excellent decision making, interpersonal and communication skills.
  • Experience and/or willingness to write funding applications.
Desired Attributes
  • Multi-domain data analysis and visualisation, ideally applied in a drug discovery/biomedical setting.
  • Understanding of more than one biomedical sciences, for example chemistry, biology, pharmacology or physiology, would be a strong advantage.
  • Familiarity with transcriptomics, proteomics and/or high content imaging data would be an advantage.
  • Experience in developing collaborative projects with external partners.
About the DDU

Established for 16 years, The Drug Discovery Unit (DDU) in the School of Life Sciences  is a unique, university-based, fully integrated, Biotech-style drug discovery operation with 130 dedicated scientists, most with a Biotech/Pharma background. The unit has purpose-built laboratories and state-of-the-art equipment for drug discovery and expertise in assay design, high-throughput and high-content screening, molecular pharmacology, medicinal, computational and analytical chemistry, DMPK and Structure Biology. The DDU develop molecules up to and including pre-clinical drug candidates.

Together with our Pharma and Product Development Partners, the DDU has delivered multiple compounds into the clinic, contributed to 7 spinouts, and has a rich portfolio of programs at the lead-optimisation and hit-to-lead stages.

The DDU has an international reputation for its work on neglected infectious diseases and is a key component of the Wellcome Centre for Anti-Infectives Research at Dundee. Our Innovative Targets Portfolio works in collaboration with leading scientists from academia to address novel targets in cancer, inflammation and neurodegeneration, leading to licencing deals and spinouts.

About The School of Life Sciences and University of Dundee

WCAIR and the DDU are embedded in the School of Life Sciences University of Dundee which was ranked the top University in the UK for Biological Sciences in the Research Excellent Framework assessment in both 2014 and 2021. Dundee has twice been named ‘the best place to work in Europe’ in a poll of scientists conducted by The Scientist magazine. You can go on a virtual visit of our labs  and find further details for School of Life Sciences facilities and support for staff .

The School is proud of its positive research culture which provides a dynamic environment supporting all to flourish. We hold an Athena Swan Silver Award (first granted in 2018, renewed in 2023). We are strong supporters of Open Research as signatories of DORA and are ranked 2nd in the World for our Open Access research (CWTS Leiden Ranking 2023).

Dundee lies in an area of outstanding natural beauty, including large sandy beaches and the Scottish Highlands less than an hour away. The city has lots to offer with fantastic attractions such as the striking V&A Dundee, the Dundee Rep, Dundee Contemporary Arts and more. Read more about the rewarding work and life environment in Dundee.

How to apply

Applicants are asked to apply on the University of Dundee job vacancy site and upload 3 documents as part of their application:

  •  CV
  • 4-page research proposal indicating broad research area/theme
  • 1-page cover letter outlining how your research synergises with and/or extends our existing strengths as well as outlining what skills, attributes and expertise you would bring more broadly to the School (e.g. in teaching, research culture, commercialisation, translation, training etc).

We are committed to providing an inclusive and diverse environment. We particularly encourage applications from those that are currently underrepresented in research, including black and minority ethnic (BME) and those from socio-economically disadvantaged backgrounds.

We welcome informal enquires and these can be directed to Mike Bodkin, Professor of Computational Drug Discovery ( or

To apply, please use the  link at the top of this page.