Multiple positions for postdoctoral research fellows are 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 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 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.

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.

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 position.

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, C++, R, etc.) and in Unix-based computing environment is desirable, but not necessary. Experience in conducting human genetics or population genetics research and analyzing large genetic datasets is also a plus, but not necessary. Passion to learn about human genetic research and to perform rigorous research is a must.

Start date is flexible throughout 2023 and 2024. A hybrid model 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 candidates should apply in Workday. In addition, please submit a CV, short (1 page) cover letter describing your research interests and fit within the lab, and contact information for 2-3 references. Potential applicants are encouraged to submit informal inquiries to Charleston Chiang at charleston.chiang@med.usc.edu.

The annual base salary range for this position is $67,000 - $72,000. 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 within previous five years Minimum Experience: 0-1 year Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures and analysis methods.