A Research Associate position is available in the lab of Dr. Charleston Chiang at USC. The Chiang lab utilizes cutting-edge analytic tools to address questions at the intersection of human medical and population genetics. In particular, we have a strong interest in using genomic data to understand the evolution and architecture of complex traits and the history of diverse human populations. These insights will be critical for future medical genetics studies and in practicing personalized medicine. The successful candidate will be involved in research from multiple projects in the lab, and will have substantial input in the nature and the direction of the ongoing research projects within the lab. The ongoing research include learning about demographic history or natural selection from genetic variation data, or understanding genetic architecture and evolutionary history of complex traits in diverse populations. Opportunities are available for research projects covering both method development and analysis of large-scale genotyping and next-generation sequencing data in humans from diverse populations.

The ongoing projects include those funded through multiple sources, and could include future funded projects or other projects conducted utilizing unrestricted funds:

(1) R01-funded: on the genetic history and genetic epidemiology of metabolic traits of Pacific Island populations (Native Hawaiians, Samoans). Will have access to newly generated whole genome sequencing data and genome-wide array data.

(2) R01-funded: on the evaluation and development of population and statistical genetic methods utilizing ancestral recombination graphs (e.g. Fan et al. AJHG 2022).

(3) R35-funded: broadly on the consequence of natural selection and demography on evolution of human traits (e.g. Chen et al. AJHG 2020), including expanding the framework to other population datasets such as Taiwan Biobank.

Across these projects, the candidate will also have access to data from Multiethnic Cohort (https://uhcancercenter.org/mec) and major biobanks, including new GWAS and WGS data being generated, and multi-omic data in pipeline.

A Ph.D. in genetics, computer science, bioinformatics, computational biology, or a related field is required. The candidate should have had some postdoctoral experience in conducting human genetics or population genetics research in Unix-based computing environment. The position expects a longer-term (> 2 yr) commitment, contingent upon sufficient progress on research projects. In addition to assisting and overseeing multiple ongoing projects in the lab, the successful candidate is expected to participate in training and mentoring students. Future transition to other positions within the Center for Genetic Epidemiology, such as faculty positions, may also be feasible.

Start date is flexible throughout 2023 and 2024. A hybrid format with some level of working from home is possible. We are actively establishing a vibrant and respectful culture in the research group. See brief notes on how we are working towards this goal here: http://chianglab.usc.edu/resources.html

Interested candidate should submit a CV, short (1-2 pages) cover letter describing your research interests and fit within the lab, and contact information for 2-3 references. Reference letters are accepted, but not required at this stage. Informal inquiry can be directly submitted to Charleston Chiang at charleston.chiang@med.usc.edu.

The annual base salary range for this position is $63,683.49 - $85,514.64. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations

Minimum Education: Ph.D. or equivalent doctorate Minimum Experience: 1 year Minimum Field of Expertise: Directly related education and experience in research specialization with advanced knowledge of equipment, procedures and analysis methods.