Daniel Stover’s research program in the Division of Medical Oncology and the Department of Biomedical Informatics at the Ohio State University seeks a computational biologist to join our team that focuses on clinical computational oncology - the application of computational approaches to leverage immense publicly-available and newly generated tumor genomic data to improve outcomes for patients with cancer.
Areas of research focus include:
1) Application of novel/emerging genomic technologies in patient and clinical trial samples to study drug resistance, patient outcomes, tumor-immune interactions, and identify novel targets;
2) Creation of new algorithms and approaches to integrate existing multi-‘omic datasets (e.g. DNA, RNA, protein, miRNA, lncRNA) to answer pressing clinical questions, with a focus on breast and other solid tumors;
3) Evolutionary profiling of tumors over time and in response to therapy via serial biopsies and cell-free DNA sequencing; and
4) Association of environmental exposures with tumor and microenvironmental features through large local and/or national clinical cohort studies.
We are committed to the intellectual growth, personal development, and advancement of all of our team members and foster a supportive, collaborative research environment. We seek a candidate committed to an inter-disciplinary, team-science approach to problem-solving who is interested in interacting with a diverse set of backgrounds (e.g. informatics, cancer biology, pathology, medical oncology, etc.). These projects are collaborative efforts between the Ohio State University, the Broad Institute, and multiple other institutions. The research environment is rich, including computational research space within Biomedical Informatics at Ohio State as well as affiliated laboratory space at the Ohio State University Comprehensive Cancer Center and clinical collaboration with the Stefanie Spielman Comprehensive Breast Center.
The candidate will:
-Establish high-throughput pipelines through development of novel algorithms and integration with existing tools;
-Help maintain, support, and document shared tools, code base, and data sets;
-Effectively display processed data to convey critical findings to data scientists, basic scientists, clinicians, and community members;
-Engage in statistical analyses of ‘omic data and clinical features; and
-Have the opportunity to pursue diverse, self-directed research opportunities - from clinical informatics to predictive modeling.
The ideal candidate should hold a masters degree or doctorate in Computer Science or Bioinformatics or Computational Biology or Statistics.
Experience with high level programming languages (e.g. R, Python, Perl), computational biological applications, and next-generation sequencing required.
Experience with manipulation, interpretation, statistical analysis, and innovative analysis of large biological datasets, preferred.
Must demonstrate outstanding personal initiative, the ability to work effectively as part of a team, and the ability to meet deadlines and efficiently multitask.
Excellent oral and written communication skills and the ability to perform both self-directed and guided research are required.
Interested applicants should contact us at email@example.com and include the following:
1. Areas of research interest in our research program
2. Brief cover letter
3. CV (Curriculum Vitae)