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Posted 1 month ago

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

LjubljanaOn-site

AI Summary

Develops, validates, and maintains cfDNA/NIPT algorithms and supports clinical WGS, defining QC metrics, performing analytical validation, and preparing regulatory documentation to ensure clinically reliable and traceable results.

About this role

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.

Tasks

  • 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.

Requirements

Required

  • 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.

Preferred

  • 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.

Nice to have

  • 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.

Benefits

  • Work on clinically impactful genomic technologies with direct patient relevance.
  • Opportunity to shape algorithms, validation strategies and production pipelines.
  • Collaboration with multidisciplinary experts in genomics, medicine, software and regulatory affairs.
  • Professional growth in a highly specialised bioinformatics environment.

If you are passionate about transforming complex sequencing data into reliable clinical insights and want to contribute to next-generation prenatal and genomic diagnostics, we would like to hear from you.

Skills

BAMCRAMDockerFASTQGitHDF5NextflowNGSNumPyPandasPythonRSciPySnakemakeStatsmodelsVCF

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