Staff Scientist, Laboratory of Translational Genomics
The Division of Cancer Epidemiology and Genetics (DCEG), National Cancer Institute (NCI), National Institutes of Health (NIH), is recruiting a staff scientist in the Laboratory of Translational Genomics (LTG).
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.
LTG conducts studies on germline and somatic genetics of cancer, including analyses of regions of the human genome conclusively identified in cancer-specific genome- wide association studies (GWAS) and family-based studies. The mission of the LTG is to understand the contribution of germline and somatic genetic variation to cancer etiology and outcomes and to elucidate underlying molecular mechanisms of these associations.
Eligibility
The successful candidate will provide bioinformatics support as a staff scientist for the research program of Dr. Ludmila Prokunina-Olsson, LTG Director and senior investigator. Her research program is focused on genetics and genomics of bladder cancer and the role of IFNL4, a type III interferon, in infection and cancer. Specifically, this support will include the following activities: accessing, extracting and preparing data for analysis, developing and maintaining bioinformatics pipelines, conducting analysis of genetic and molecular epidemiology data within and across omic platforms including use of integrative analytic methods, organizing results into clear presentations and concise summaries of work, and maintaining experience with state-of-the-art bioinformatics tools and data repositories. The candidate will also participate in mentoring and training next generation of scientists.
The successful candidate must hold a doctoral degree in genetics, genomics, bioinformatics, biostatistics, computer science, computational biology or other related disciplines. The ability to 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. The successful applicant will possess many (although not necessarily all) of the following skills: the ability to program efficiently in at least one programming language (e.g., Python, Perl, C/C++, and/or JAVA); experience with processing and analyzing large datasets for at least one of the following: GWAS, transcriptomics, methylomics, metabolomics, microbiomics, next-generation sequencing; experience with publicly available software through GitHub and other sources; proficiency in R/Bioconductor; proficiency with public bioinformatics databases (e.g., UCSC Genome Browser, TCGA, ENCODE, 1000 Genomes, dbGAP, GTEX, SRA NCBI); proficiency with bash scripting and working in a Linux environment (especially a computer cluster environment); proficiency with core statistical and bioinformatics methods (e.g. linear regression, logistic regression, eQTL analysis, LDscore regression, credible set and colocalization analysis, etc.); and a demonstrated ability to self-educate in current and evolving bioinformatics techniques and resources. The successful candidate will conduct/supervise the analysis of data generated by functional genomic methods such as CRISPR and MPRA screens, chromatin interaction and splicing assays.
How to Apply
Applications will be accepted through May 28, 2024. 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. This position is subject to a background investigation. Salary is commensurate with research experience.
Interested individuals should send a cover letter, curriculum vitae, brief summary of research interests and experience, and two letters of reference via email to: Tammy Perdikis, LTG.