4806991 Postdoctoral Fellow, Computational Biology

The Simulation and Modeling Sciences group is seeking an outstanding postdoctoral researcher to join us to help advance statistics and machine learning for computational biology in the area of gene therapies and other oligonucleotide-based modalities. We are looking for applicants with a research background in biostatistics and machine learning, familiarity with computational biology, and able to develop new algorithms for practical applications. We offer a supportive and collaborative environment for cutting-edge interdisciplinary research.


Role Responsibilities

  • Develop and apply statistical and machine learning algorithms for multi-omics high-throughput datasets including short and long-read sequencing data.
  • Write well-documented code individually and collaboratively within a high-performance scientific computing environment.
  • Effectively communicate the advantages and caveats of developed algorithms to internal audiences with diverse backgrounds.
  • Collaborate with computational and experimental scientists located at multiple locations.
  • Publish articles in top peer-reviewed journals and deliver scientific and technical presentations at internal and external venues.


Basic Qualifications

  • D. in biostatistics, computer sciences, or a related technical field.
  • Familiarity with next-generation sequencing technology.
  • Well-cited journal publications.
  • Programming experience in Python, R, or equivalent languages.
  • Strong oral and written communication skills to work in a team-based environment.


Preferred Qualifications

  • Research experience in the analysis of high-throughput sequencing data.
  • Advanced coursework in molecular biology.
  • Familiarity with gene therapies and other oligonucleotide-based
  • Experience with a cloud-based computational environment such as a SLURM based cluster