Post-doctoral fellow

We are looking for a highly-motivated postdoctoral fellow with strong background in statistics and computation, programming skills, and/or population genetics with an ability to perform independent research. Potential projects include, but are not limited to:

  1. Statistical methods for genetic analysis of complex traits.
  2. Computational methods to study admixture at diverse time-scales and its impact on phenotype.
  3. Methods for analyzing genomic time series.
  4. Inferring demographic history from genome sequences.
  5. Algorithmic and inferential problems in scaling these methods to massive datasets.

Our lab is tightly integrated with a vibrant research community in bioinformatics, population and medical genetics at UCLA. We collaborate closely with many other labs in computer science (Eskin, Halperin), human genetics (Pasaniuc, Freimer, Flint, Sul) and population genetics (Lohmueller).

Candidates must hold a Ph.D. in computer science, statistics, bioinformatics, biostatistics, computational biology, or a related quantitative field and have a strong publication record. The position is available for 1 year and may be continued for an additional year contingent on successful progress and available funding.

Interested candidates should email Sriram Sankararaman ( with their CVs, research statements and names of three references.

Ph.D. students

We are looking for Ph.D. students with strong computional and statisical backgrounds. Ph.D. students can join our lab through the Computer Science, Bioinformatics, or Genetics and Genomics graduate programs.