Clinical Bioinformatics Scientist – NIPT & cfDNA

About the role

We are developing clinical‑grade genomic solutions based on cell‑free DNA (cfDNA) and next‑generation sequencing (NGS). The Clinical Bioinformatics Scientist will design, validate and maintain algorithms for non‑invasive prenatal testing (NIPT) and support germline/clinical whole‑genome sequencing (WGS) workflows.

Key responsibilities

• Develop and optimise cfDNA/NIPT algorithms for fetal aneuploidy, sex‑chromosome abnormalities, sub‑chromosomal CNVs/microdeletions and fetal‑fraction estimation.
• Build and maintain normalisation and calibration pipelines (panel‑of‑normals, coverage references, GC correction, z‑scoring, batch/drift correction).
• Define QC metrics, thresholds and acceptance criteria using data‑driven sensitivity/specificity analysis.
• Investigate analytical artefacts, pipeline failures and performance drift; perform root‑cause analysis and implement corrective actions.
• Support clinical WGS pipelines including QC, SNV/indel/CNV/SV detection, annotation and prioritisation.
• Ensure reproducible, version‑controlled, traceable analyses suitable for clinical and regulatory environments.
• Prepare analytical validation reports, technical documentation and method‑change justifications for audits.
• Transfer validated methods into production and collaborate with molecular biology, clinical, software, QA and regulatory teams.

Required profile

• MSc or PhD in bioinformatics, computational biology, statistics, mathematics, computer science, genetics or a related field.
• Proven experience debugging and stabilising quantitative genomic pipelines (batch effects, bias correction, calibration, QC).
• Strong applied statistics knowledge (normalisation, robust estimators, ROC analysis, rare‑event detection).
• Excellent scientific English and ability to work independently in interdisciplinary teams.

Required skills

• Python (numpy, pandas, scipy, statsmodels)
• R (knowledge)
• Linux workflow development, Git version control
• NGS data formats: FASTQ, BAM, CRAM, VCF, coverage files, HDF5
• Workflow managers: Nextflow, Snakemake
• Containerisation: Docker
• CI/CD pipelines
• HPC / cloud computing and parallel processing
• Statistical modelling and machine‑learning techniques