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 have substantial input in the nature and the direction of the ongoing research projects within the lab and will be encouraged to explore projects that broadly fit within the lab’s research interests and funded R35 and R01 grants. These goals 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 both method development as well as analysis of large-scale genotyping and next-generation sequencing data in humans from diverse populations. 

The candidate (either postdoc or research scientist) can be funded through multiple sources:

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

(2) R01: on method development for statistical and population genetic applications based on the ancestral recombination graph (e.g. Fan et al. AJHG 2022).

(3) R35: 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.

(4) Unrestricted funds: there is room for postdocs and scientists to explore research topic broadly consistent with the research direction of the lab, through either method development or empirical explorations.

The candidate will also have access to data in Multiethnic Cohort (https://uhcancercenter.org/mec), including new GWAS and WGS data being generated, and multi-omic data in pipeline. Broad mentorship across different fields (epidemiology, statistics, population genetics, etc)

Postdoc position is for 1-3 yrs depending on the career goals of the candidate. Position is extendable at the end of the initial appointment. Salary starting above the NIH postdoc scale (step 7; > $66,600 per year), commensurate with experience and expertise. While postdocs are considered a transient phase of one's career, we also value stability. There will be opportunities to transition to staff scientist or faculty position within the Center for Genetic Epidemiology at USC for the promising scholars.

More experienced applicant may also consider applying to career-track research scientist position. The position expects a longer term commitment, with higher salary start point. Future transition to other positions within the Center for Genetic Epidemiology is also feasible.

Because of the various ways the position can be funded, start date is flexible throughout 2023, for both types of positions. Some level of working from home is possible, and completely remote options (within continental U.S.) is negotiable based on the candidate's situation (such as due to family or two body situations). 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

Candidates should have a Ph.D. in genetics, computer science, bioinformatics, computational biology, or a related field. Proficiency in one or more programming languages (e.g. python, perl, C++, R, etc.) and in Unix-based computing environment is desirable. Experience in conducting human genetics or population genetics research and analyzing large genetic datasets is a plus.

Interested candidates 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. Material should be directly submitted to Charleston Chiang at charleston.chiang@med.usc.edu.