Staff Scientist, Occupational and Environmental Epidemiology Branch
The Occupational and Environmental Epidemiology Branch (OEEB) is recruiting a computational analyst/bioinformatician (staff scientist) for the analysis of large-scale genetic association studies for cancer and related outcomes.
Who We Are
DCEG is committed to discovering and understanding the genetic architecture of cancer, including the identification of common and rare loci for cancer risk, exploration of underlying functional mechanisms and the impact of environmental exposures, and use of genetic variants for risk stratification and prevention. For more information visit the DCEG website.
The successful candidate will provide bioinformatic analytical support for genetics projects under Dr. Sonja Berndt. The staff scientist will be expected to perform a range of genetic and bioinformatic analyses including: imputation, population structure assessment, variant association testing, LD-score regression, fine-mapping across different ancestries, rare variant burden testing, pathway and other related analyses for genome-wide association studies (GWAS); utilize and test new open-source programs for analysis of GWAS and next generation sequencing (NGS) data; develop and maintain necessary bioinformatics pipelines for conducting state-of-the art genetic analyses; process and utilize publicly available datasets (e.g., UK Biobank) for analyses; organize and maintain data and results in a clear and consistent manner; and grow and maintain experience with state-of-the-art bioinformatics tools and data repositories.
The successful candidate must hold a doctoral degree in bioinformatics, biostatistics, computer science, computational biology or other related disciplines. The candidate must have experience processing and analyzing large genetic datasets and possess expertise in algorithmic implementation, statistical programming and data manipulation and proficiency in programming using Python, Perl, R, C/C++, and/or JAVA. The successful applicant should possess many of the following skills: experience with open-source bioinformatic tools for genetic analyses (e.g., REGENIE, GCTA, MR-MEGA, FINEMAP, LDSC); proficiency in R/Bioconductor; experience with public bioinformatic/genetic databases (e.g., dbGAP, TCGA, gnomAD, 1000 Genomes, and GTEx); experience with bash scripting and working in a Linux environment (especially a computer cluster environment); experience with core statistical methods (e.g. linear regression, logistic regression, linear mixed models, etc.); and a demonstrated ability to self-educate in current and evolving bioinformatics techniques and resources. The ability to work well with others and communicate effectively in speech and in writing is important, as demonstrated by a track record of publications in peer-reviewed literature as part of a research team or collaborative projects.
How to Apply
Applications will be accepted on a rolling basis until a suitable applicant is found. Selection for this position will be based solely on merit, with no discrimination for non-merit reasons such as race, color, religion, gender, sexual orientation, national origin, political affiliation, marital status, disability, age, or membership or non-membership in an employee organization. NIH encourages the application and nomination of qualified women, minorities and individuals with disabilities. NIH provides reasonable accommodations to applicants with disabilities. If you require reasonable accommodation during any part of the application and hiring process, please notify us. The decision on granting reasonable accommodation will be made on a case-by-case basis. This position is subject to a background investigation. Salary is commensurate with research and experience.
Interested individuals should send a cover letter, curriculum vitae, brief summary of research interests and experience, and two letters of reference to:
The closing date for applications is August 15th.
HHS, NIH, and NCI are Equal Opportunity Employers