Collaboration

I work with biotech companies, pharmaceutical R&D teams, and academic research groups as a senior external partner on projects involving complex omics datasets.

My role combines scientific interpretation, strategic input, and hands-on analysis, engaging at the level each project requires, from focused analytical work to scientific leadership across a research programme.

Getting involved early, at the study design stage, often leads to better outcomes. I am happy to advise on experimental design, technology selection, and analytical strategy before data generation begins.

Engagement models

Collaborations are flexible and structured around the needs of the project and team.

Project-based collaboration

Focused engagements centred on a specific dataset or research question. I lead the analysis and interpretation, work closely with the team throughout, and deliver conclusions that directly inform experimental direction and project decisions.

Hourly-based collaboration

For teams that need flexible involvement during active project phases, hourly-based collaboration allows continuous input as datasets evolve and interpretation develops over time.

Long-term scientific partnership

Some collaborations extend across multiple datasets or studies, providing continuous senior bioinformatics support throughout a research programme. This model works well for teams with recurring omics analysis needs but without a permanent senior bioinformatician in-house.

Fractional or interim bioinformatics lead

For organisations building or scaling their bioinformatics capability, I can take on a fractional or interim leadership role, owning the bioinformatics strategy, structuring workflows, aligning the team around analytical standards, and acting as the senior scientific point of contact for omics data across projects.

Working as part of the team

Although I work independently, I integrate closely with the research teams I support. Rather than operating as a detached external analysis service, I work directly with experimental researchers, project scientists, and internal bioinformatics teams. This type of collaboration keeps the analysis tightly connected to the experimental context and ensures conclusions are meaningful for the broader research programme.

This is particularly valuable for industry teams that need senior bioinformatics expertise without the commitment of a permanent hire, and for academic groups tackling datasets that require dedicated computational leadership.

How I support teams

Depending on the engagement, my involvement can span the full project lifecycle or focus on a specific phase where senior bioinformatics input is most needed.

End-to-end omics project support, from study design to biological interpretation
Multi-omics integration and systems-level interpretation
Decision-oriented reporting for discovery and translational teams
Short-term computational capacity during peak project phases
Training and mentoring researchers in bioinformatics data analysis

More about my expertise →

Scientific contributions

Depending on the project, my role may include:

Leading the analysis and interpretation of complex multi-omics datasets
Advising on study design, technology selection, and analytical strategy upstream of data generation
Integrating datasets across technologies to uncover systems-level biological mechanisms
Translating results into biologically meaningful conclusions that inform research strategy
Presenting findings through reports, figures, and scientific discussions
Mentoring and aligning internal team members around the analytical approach

Training and mentoring

In addition to direct project work, I support teams in building internal bioinformatics capabilities. This includes training researchers in omics data analysis and interpretation, guidance on computational workflows and reproducible analysis practices, and mentoring junior bioinformaticians. Sessions are tailored to the experience level and research focus of the team.

Getting started

If you are working with complex omics datasets and would like to discuss a potential collaboration, feel free to get in touch.

Initial conversations usually focus on the biological question, the type of data involved, and how analysis and interpretation could support the project.