Summary

The Sedlazeck Lab is seeking a highly motivated Staff Scientist with strong computational and algorithmic expertise to lead and support cutting-edge research in long-read genomics, tandem repeat (TR) analysis, and population-scale variant discovery. Our group develops novel methods and performs large-scale analyses across diverse cohorts, leveraging PacBio HiFi, Oxford Nanopore, and graph-based genome technologies.

Job Duties

• Develops, implements, and optimizes algorithms and computational methods for structural variant (SV), tandem repeat (TR), and methylation analysis in long-read sequencing data. 
• Leads population-scale analyses involving thousands of long-read genomes, including data QC, variant calling, benchmarking, and integration across platforms.
• Designs and executes computational workflows for SV and TR discovery, merging, harmonization, and interpretation across large cohorts.
• Works independently to drive multiple concurrent projects, including collaborations with national and international consortia (e.g., All of Us, TOPMed, GREGoR).
• Contributes to manuscript writing, grant applications, and presentation of results at internal and external meetings.
• Mentors trainees and support a collaborative, high-impact research environment. 

Minimum Qualifications

• MD or Ph.D. in Basic Science, Health Science, or a related field.
• No experience required.

Preferred Qualifications

• Ph.D. in Chemistry, Computational Sciences, Computational Biology, Structural Biology, Computer Science, Bioinformatics, Statistics, or related disciplines. May also include Ph.D. in Biology or Biomedical Sciences in combination with an M.S. or extensive multidisciplinary experience in one of the above quantitative fields