Gabriel Mateus Bernardo Harrington
Data Analyst / Computational Biologist
mateusharrington.com | GitHub: H-Mateus | LinkedIn: gmb-harrington | ORCID: 0000-0001-6075-3619 | United Kingdom
Summary
Scientist-turned-analyst with 7+ years’ experience in high-dimensional biological data analysis, reproducible research, and statistical modelling. Expertise in R, bash, super computing and omics data (transcriptomics, proteomics, EHR). Passionate about clean, reproducible pipelines and cross-functional collaboration. Seeking roles where I can apply my analytical skills to impactful, real-world problems.
Employment
Cardiff University, UK — Research Associate (Bioinformatician) - 2021–Present
- Analysed multi-omics data in Alzheimer’s research; developed pipelines using R and bash on HPC.
- Delivered training in reproducibility, version control, and workflow automation.
Bionics Institute, Australia — Research Assistant - 2016–2018
- Led wet lab work on optogenetic project for cochlear implants.
- Lab work included animal handling, immunohistochemistry, microscopy, surgery and tissue sectioning.
Selected Projects & Achievements
- Alzheimer’s Disease single-cell RNA-seq analysis: Built reproducible workflows to analyse single nuclei sequencing data, including differential expression, genetic risk and pseudotime analysis.
- Spinal Cord Injury Prognostic Modelling: Applied multilevel and classical statistical models to proteomic and EHR data.
- Shiny Applications: Created interactive apps for transcriptomic and prognostic model exploration.
- Research Software Champion: Led reproducibility training and open science efforts across the UK DRI.
- Community Leadership: Chaired the UK DRI ECR Informatics Committee.
Skills
Programming & Tools: R, Bash, SQL, Git, Nextflow, Docker/Singularity, SLURM, Quarto/RMarkdown, Snakemake (basic), Python (intermediate)
Data Analysis: Genomics, Proteomics, Electronic Health Records, Bayesian/Frequentist Statistics, Differential Expression, Data Visualisation
Workflows & Reproducibility: GitHub/GitLab, Containerisation, HPC job scheduling, Workflow automation, FAIR data practices
Communication & Teaching: R training for MSc students, workshop delivery, cross-disciplinary collaboration
Languages: English (native), Portuguese (intermediate), Greek (beginner)
Education
PhD in Biomedical Engineering — Keele University, UK (2018–2021)
Focus: Prognostic modelling in spinal cord injury using omics and EHR data.
BSc (Hons) Biological Sciences — Lancaster University, UK (2013–2016)
Awards & Fellowships
- DPMCN ECR TADA Travel Grant – £750 (2025)
- Associate Fellowship – Advance HE (2024)
- Winning Team – DEMON Network NeuroHack (2022)
- Winning Team – Race Against Dementia Accelerator (2021)
- EPSRC CDT Grant – £5000 (2021)
- Duke of Edinburgh Silver Award (2010)
Selected Publications
- Bernardo Harrington, G. M. et al. (2024). A Comprehensive Proteomic and Bioinformatic Analysis of Human Spinal Cord Injury Plasma Identifies Proteins Associated with the Complement Cascade and Liver Function as Potential Prognostic Indicators of Neurological Outcome. Journal of Neurotrauma
- Bernardo Harrington, G. M. et al. (In prep). Paired Vascular-Parenchymal Single Nuclei Sequencing Reveals Perturbed Endothelial-to-Mesenchymal Transition in Alzheimer’s Disease.
- Full list: ORCID Profile
Outreach & Teaching
- Lecturer for MSc Bioinformatics students (R programming, stats, reproducibility)
- Trainer at EMBL course on dementia research
- Hosted livestream fundraiser for ARUK (~10K views)
- Speaker at international and UK-based research conferences