Bioinformatics Scientist & Consultant
Bioinformatics pipelines, genomics and scientific computing
I design and maintain reproducible workflows for genomic data, mainly with Nextflow, Python, containers, HPC and Azure Batch.
Get in touchBioinformatics, from analysis to production workflows
I am a bioinformatics scientist and independent consultant with a PhD and more than 15 years of experience in genomics. My work combines biological data analysis with workflow architecture, scientific software development and computing infrastructure.
I design, implement and maintain reproducible analysis systems rather than simply operating existing bioinformatics tools. I mainly work with Nextflow, Python, Docker, HPC systems and Azure Batch.
What I work on
Workflow development
Nextflow and Snakemake workflows for genomics, pathogen genomics, transcriptomics, metagenomics, AMR and related analyses. Reproducibility, containers and execution across local, HPC and cloud environments.
Genomics & data analysis
Analysis and automation of genomic and multi-omics data using Python, R and command-line bioinformatics tools.
Scientific computing
Docker, HPC, Azure Batch, container and resource configuration, workflow deployment and debugging, including performance and resource issues in production bioinformatics pipelines.
Selected work — European Food Safety Authority (EFSA)
Bioinformatics workflows and scientific computing at EFSA
As an external contractor for EFSA, I work on high-throughput whole-genome sequencing pipelines for bacteria, fungi and viruses. The work includes production WGS workflows, debugging container storage constraints, Nextflow resource allocation and Azure Batch execution issues.
This includes investigating Docker containerization and nextflow.config parameters, including custom Docker image mounts to work around Azure VM storage limits and rebalancing how the workload is distributed.
I also develop machine-learning workflows for protein sequence analysis, including ensemble modelling, cross-validation and explainability, with a focus on reproducible training and prediction pipelines.
For selected development tasks, I use agentic AI workflows for implementation, refactoring, testing and debugging. The workflow may involve multiple specialised agents, with architecture, validation, reproducibility and scientific interpretation remaining under direct technical oversight.
Technical expertise
Workflow Engineering
- Nextflow
- Snakemake
- Reproducible Pipelines
- Workflow Testing
Scientific Computing
- Azure Batch
- HPC
- Docker
- Linux
- Resource Optimization
Data & Modelling
- Python
- R
- Machine Learning
- Ensemble Models
- Explainability
Bioinformatics
- Genomics
- Pathogen Genomics
- Metagenomics
- Transcriptomics
- AMR
Get in touch
I'm available for bioinformatics, workflow development and scientific computing projects. If you'd like to discuss a project, feel free to get in touch.
Schedule a call ↗or send a message directly