The Applied Research Scientist position will support two faculty research teams - the Gerke and Schmit labs - in the Department of Cancer Epidemiology. Dr. Travis Gerke and Dr. Stephanie Schmit are both integrative molecular epidemiologists undertaking cross-disciplinary work at the intersection of cancer epidemiology, biostatistics, genetics, and computational biology.
Dr. Gerke's research portfolio focuses on identifying tumor-based biomarkers of aggressive prostate and thyroid cancers. Dr. Gerke also conducts novel methodological research to optimize the use of large-scale genomics datasets and to utilize clinical trial data for determining optimal therapy sequences. Dr. Schmit's research combines wet and dry lab approaches to better understand the roles of genetic susceptibility, molecular markers, and environmental factors in the development of colorectal cancer (CRC) and the modulation of disease progression and outcomes. Active research projects include studies on the role of host immune responses and the microbiome in the adenoma-carcinoma transition as well as their contributions to CRC survival and several projects associated with large genome-wide association study consortia. In both labs, there are opportunities to work on health disparities-related projects.
This position may be compared to a staff scientist role - an essential contributor to analysis, writing, and grant preparation for on-going and future research projects. This position will have ample opportunities for co-authorship and other documentable career-enhancing activities.
· Independently conducts advanced analyses of high-dimensional 'omics' datasets (e.g. genotype, gene expression, whole exome sequence, microbiome, immunoprofiling), both publicly available and internally generated.
· Writes and prepares manuscripts for a variety of research studies.
· Generates scientific sections of grant applications with appropriate guidance, including preliminary data.
· Learns to apply novel, cutting- edge biostatistical and bioinformatic methodologies to cancer epidemiology studies.
· Manages the scientific advancement of multiple studies simultaneously.
The Ideal Candidate
· PhD in genetic epidemiology, statistical genetics, quantitative human genetics, statistics/biostatistics, bioinformatics, molecular or computational biology, computer science, or a closely aligned quantitative field.
· Applicants with a medical background but proven strength, experience, and strong interest in statistical analysis may be considered.
· Extensive computational and programming experience, including demonstrated proficiency in Python or Perl and R. Strong familiarity with high performance computing in a Unix environment.
· Facility with managing and analyzing publicly-available datasets, such as TCGA and ArrayExpress.
· Experience conducting genotype QC and imputation, GWAS analysis, large-scale NGS data analysis (FASTQ through variant calling or differential expression), and deconvolution of gene expression from heterogeneous cell populations.
· Demonstrated experience collaborating in a multidisciplinary environment.
· In-depth knowledge of how epidemiological research is conducted.
· A commitment to reproducible and open science workflows.
· A critical, independent, and creative thinker.
· A professional, personable, organized individual with research experience in the academic setting.
· Excellent oral and written communication skills. Grant writing experience is highly desired.
· Under the direction and guided by the faculty investigators, performs research and related support activities including, (a) development and implementation of research projects; (b) preparation of reports, manuscripts, and grants and (c) presentation of research at scientific meetings
· Analysis of genome-wide association study (GWAS) data and biological data derived from other high- throughput 'omics' technologies.
· Development, computer programming, and application of statistical methods for molecular epidemiology studies.
· Interacts closely with Investigators and their collaborators in consortium settings.
· Assists in planning and developing research projects within the laboratory under the Investigator's direction.
· Maintains research skills, and acquires new ones as necessary.
· Limited degree of supervision is required for the analysis of data and documentation of results.
· Maintains membership and regularly attends appropriate professional associations, conferences, workshops, lectures, and seminars as supported by the overseeing Investigators.
· Maintains familiarity with cutting edge laboratory trends and techniques.