Research Scientist-Medical Oncology

The Ohio State University

4d•Onsite

About The Position

The Hayes Lab in the Department of Internal Medicine, Division of Medical Oncology at The Ohio State University is seeking a Research Scientist to serve as an expert resource in computational biology, cancer genomics, bioinformatics, and translational oncology within the OSUCCC research environment. The position will lead independent and collaborative projects involving cancer biology, molecular subtyping, genomic and transcriptomic profiling, therapeutic response and resistance, biomarker discovery, and integrative multi-omics analysis across diverse cancer types. The Research Scientist will develop hypotheses and analytical strategies; establish and optimize reproducible bioinformatic workflows; oversee data processing, analysis, interpretation, visualization, and reporting; and provide scientific guidance on study design, genomic and transcriptomic analysis, multi-omics integration, statistical modeling, machine learning, and emerging computational technologies. The position will collaborate with multidisciplinary teams to establish research priorities, interpret complex biological, genomic, and clinical data, troubleshoot technical problems, and develop new research directions. The Research Scientist will remain current with relevant literature and methodological advances and make recommendations regarding research strategies and analytical procedures. The Research Scientist will prepare manuscripts, abstracts, project reports, and grant proposals; present findings at institutional and national or international conferences; and contribute to workshops, lectures, and seminars. The position may develop and submit extramural grant proposals as principal investigator, co-investigator, or key personnel, as appropriate under institutional policy, and may assist with grant administration, budget management, progress reports, and compliance documentation. The Research Scientist will supervise, mentor, and train junior investigators, postdoctoral researchers, graduate students, research staff, and analysts. This includes advising on study design, computational methods, data analysis, interpretation, manuscript preparation, presentations, and career development.

Requirements

Doctoral degree required in computational biology, bioinformatics, biostatistics, computer science, biomedical informatics, genomics, systems biology, quantitative biology, biomedical sciences, or a related field.
Three or more years of experience in computational biology, bioinformatics, genomics, cancer research, or analysis of high-dimensional biological data is required.
Demonstrate the ability to function as an independent and productive researcher.
Evidence of peer-reviewed publications.
Evidence of presentations at professional societies or national or international conferences.
Evidence of development of analytical methods, computational workflows, datasets, software tools, or research resources.
Evidence of contribution to grant-funded research programs.
Demonstrated ability to solve important biological, translational, or applied research problems.

Nice To Haves

Translational experience integrating molecular data with clinical, pathologic, treatment, or outcome data is preferred.
Experience in cancer genomics, transcriptomics, next-generation sequencing analysis, multi-omics integration, clinical trial data analysis, human cancer datasets, molecular subtyping, biomarker discovery, or computational analysis of clinically annotated datasets is preferred.
Experience with manuscript preparation, grant writing, collaborative project leadership, and mentoring is also preferred.

Responsibilities

Lead independent and collaborative projects involving cancer biology, molecular subtyping, genomic and transcriptomic profiling, therapeutic response and resistance, biomarker discovery, and integrative multi-omics analysis across diverse cancer types.
Develop hypotheses and analytical strategies.
Establish and optimize reproducible bioinformatic workflows.
Oversee data processing, analysis, interpretation, visualization, and reporting.
Provide scientific guidance on study design, genomic and transcriptomic analysis, multi-omics integration, statistical modeling, machine learning, and emerging computational technologies.
Collaborate with multidisciplinary teams to establish research priorities, interpret complex biological, genomic, and clinical data, troubleshoot technical problems, and develop new research directions.
Remain current with relevant literature and methodological advances and make recommendations regarding research strategies and analytical procedures.
Prepare manuscripts, abstracts, project reports, and grant proposals.
Present findings at institutional and national or international conferences.
Contribute to workshops, lectures, and seminars.
Develop and submit extramural grant proposals as principal investigator, co-investigator, or key personnel, as appropriate under institutional policy.
Assist with grant administration, budget management, progress reports, and compliance documentation.
Supervise, mentor, and train junior investigators, postdoctoral researchers, graduate students, research staff, and analysts.
Advise on study design, computational methods, data analysis, interpretation, manuscript preparation, presentations, and career development.