UNIV - Open Rank Faculty - Department of Radiation Medicine

About the role

We are recruiting a Bioinformatics Lead to build and continuously improve the computational analysis platform supporting high-sensitivity circulating tumor DNA (ctDNA) assay development and translational clinical research.

Responsibilities

• Pipeline development and analysis support
• Develop and maintain computational workflows supporting ctDNA-focused targeted sequencing analyses.
• Implement robust quality control metrics, acceptance criteria, and failure triage processes for high-depth sequencing runs.
• Generate analysis outputs and summaries to support translational studies, manuscripts, and grant applications.
• Contribute to continuous improvement of analytic performance (sensitivity/specificity) for ultra-low VAF detection and MRD-related applications.
• Translational collaboration
• Partner with wet-lab and clinical teams to align assay design, sample processing, and analytic outputs; participate in troubleshooting and iterative optimization.
• Support study design discussions, analytic endpoint definitions, and interpretation of results for translational research programs.
• Data stewardship
• Support best practices for data governance, provenance, documentation, and reproducibility in handling human genomic data.
• Work with institutional resources to implement secure computational environments and appropriate data access practices.
• Mentorship and program growth
• Mentor junior analysts as the program grows; contribute to hiring, onboarding, and training as needed.
• Help establish standards for analytic workflows, documentation, and communication across the research team.

Qualifications

• PhD in Bioinformatics, Computational Biology, Genetics/Genomics, Computer Science, Biostatistics, or related field; or MS with substantial relevant experience (track/title commensurate with credentials).
• Demonstrated experience analyzing ctDNA NGS data, including ultra-low allele fraction detection and/or MRD-related workflows.
• Strong NGS fundamentals: alignment, variant calling, QC, annotation, and interpretation-ready output generation.
• Proficiency in Python and/or R; strong comfort with Linux/Unix environments.
• Experience implementing reproducible analytic workflows and maintaining code in collaborative environments (e.g., version control).
• Track record of delivering robust pipelines used repeatedly for real datasets (not one-off scripts).
• Strong communication skills and ability to operate effectively in a multidisciplinary translational environment.

Preferred Qualifications

• Method development experience related to error suppression, background error modeling, consensus approaches, or sensitivity/specificity benchmarking for ultra-low VAF detection.
• Experience designing computational validation plans (e.g., precision/recall, LOD, reproducibility) and supporting assay/pipeline iteration.
• Experience with FFPE tumor tissue sequencing analysis and variant calling (or similar challenging specimen types with artifact-aware calling and QC).
• Familiarity with HIPAA-aligned compute environments and practices for handling human genomic data; experience with secure cloud environments (AWS/GCP/Azure).
• Experience working in or alongside clinical genomics settings and documentation practices supportive of eventual clinical validation.
• Experience mentoring analysts/engineers and/or leading pipeline development across multiple projects.