Clinical Bioinformatics Scientist - NIPT & cfDNA (with clinical WGS and IVDR documentation)

We are developing clinical-grade genomic solutions based on cfDNA and NGS data. We are looking for a Clinical Bioinformatics Scientist to build, validate and maintain robust algorithms for NIPT, with additional involvement in germline/clinical WGS. The role combines quantitative method development, analytical validation and regulatory documentation to ensure reliable, traceable and clinically defensible results.

• Develop and optimise cfDNA/NIPT algorithms for fetal signal detection, including aneuploidy (T13/18/21), sex-chromosome abnormalities, sub-chromosomal CNVs/microdeletions and fetal fraction estimation.
• Build and maintain normalization and calibration approaches (panel-of-normals, coverage references, GC correction, z-scoring, batch/drift correction) and understand their validation impact.
• Define QC metrics, thresholds and acceptance criteria using data-driven sensitivity/specificity evaluation.
• Investigate analytical artifacts, pipeline failures and performance drift; perform root-cause analysis and implement corrective actions.
• Support clinical WGS workflows including QC, SNV/indel/CNV/SV detection, annotation and prioritisation.
• Ensure reproducible, version-controlled and traceable analyses suitable for clinical and regulatory environments.
• Prepare analytical validation reports, technical documentation and method-change justifications for audits.
• Transfer new methods into validated production environments and collaborate with molecular biology, clinical, software, QA and regulatory teams.

• MSc or PhD in bioinformatics, computational biology, statistics, mathematics, computer science, genetics or related field.
• Proven experience debugging and stabilising quantitative genomic pipelines (batch effects, bias correction, calibration, QC).
• Strong applied statistics: normalization, calibration, robust estimators, z-scores, ROC/performance evaluation and rare-event detection.
• Strong Python skills (numpy/pandas/scipy/statsmodels or equivalent); R knowledge is a plus.
• Hands-on NGS experience with genomic data formats (FASTQ/BAM/CRAM, VCF, coverage data, HDF5) and large-scale datasets.
• Experience with reproducible Linux workflows, git, testing and structured documentation.
• Ability to translate complex analyses into clear scientific and regulatory documentation.
• Excellent scientific English and ability to work independently in interdisciplinary teams.

• Direct cfDNA/NIPT/prenatal genetics experience, including fetal fraction and aneuploidy/CNV detection.
• Experience with cfDNA fragmentomics and bias-correction methods.
• Experience in regulated IVD/clinical environments and knowledge of IVDR, ISO 13485, IEC 62304 or ISO 14971.

• End-to-end clinical WGS pipeline experience.
• Nextflow/Snakemake, Docker/containers, CI/CD.
• HPC/cloud computing or parallel processing.
• Statistical modelling or ML approaches with proven clinical performance benefits.
• Experience with genomic data governance and sensitive clinical data.