Jose Ramon Jeronimo Liñan

Bridging biology and computation to turn biological data into decisions

As a bioprocess engineer, I bring the biological understanding behind the data — along with laboratory and industrial experience — to my computational biology work

Vienna, Austria EU national, no sponsorship needed Part-time now, full-time from November 2026

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Bridge

Bioprocess engineering taught me to read biological systems under pressure — optimizing fermentation runs, designing controlled experiments, and translating batch data into process decisions. That training built a skill most computational pipelines lack: the ability to look at a statistical output and ask what it means for the organism, not just the model. I build workflows with that lens built in, so the results translate into actions, not just plots.

What I bring:

  • Experimental design experience that catches data quality problems before they reach the pipeline
  • The biological grounding to interpret computational outputs in context — not just report them
  • Industrial and research exposure across fermentation, microbial systems, and omics

Projects

gemAGT

Manually discovering where a metabolic pathway is broken is painful. GemAGT provides the reactions that are causing the model to fail, shortening the discovery time from hours of manual search to minutes of automatic computing

Live
Python COBRApy

biopipes

Set of sequencing data pipelines that converge into a multiomics integration pipeline and plot generation. Currently supporting RNAseq, ATACseq and WGS.

In Progress
R bash

Single-cell data analysis

Notebook used to analyze a given single-cell sequencing data set provided as an assignment for a lecture

Live
Python scanpy scVI CellTypist

Dark proteome analysis using Machine Learning

Comparative ML pipeline on the A. thaliana PeptideAtlas dataset, classifying protein detectability from three sequence-derived and two transcript-level properties

Live
Python scikit-learn

Skills

Single-cell analysis

scanpy scVI CellTypist Scrublet Leiden UMAP HVG selection batch integration AnnData / .h5ad

Machine learning

scikit-learn PCA stratified & nested CV pipeline preprocessing class imbalance ROC & threshold tuning model interpretation

Metabolic modelling

COBRApy gapseq genome-scale models model curation

Sequencing pipelines

bash R samtools bowtie2 fastqc fastp RNAseq / ATACseq / WGS multiomics integration

Data handling & visualisation

Python pandas numpy SciPy matplotlib seaborn streamlit

Environments

GitHub JupyterLab server remote Linux server HPC

Contact

Bioinformatics, computational biology and life-science data science roles. Also open to PhD positions and industry internships.

Based in
Vienna, Austria
Work eligibility
Spanish citizen, EU national - no visa or sponsorship required
Availability
Available part-time now. Full-time from November 2026.
Studying
M.Sc. OMICs Technologies and Data Science in Biomedicine, IMC Krems. Master Thesis project at the University of Vienna until November 2026.
Languages
Spanish (native), English (professional), German (B1)