Research Associate, Research Scientist, Clinical Research

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The University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (UMGCCC) is a National Cancer Institute-designated comprehensive cancer center, a distinction that places it in the top tier of cancer centers throughout the country.

Located on the medical campus of the University of Maryland at Baltimore, UMGCCC brings together expert researchers and clinicians from the University of Maryland School of Medicine to collaborate on preventing, detecting, and treating cancer. As part of an academic medical community, UMGCCC integrates cutting-edge cancer treatment with leadership in cancer research and a commitment to medical education.

The Greenebaum Comprehensive Cancer Center and the Division of Biostatistics and Bioinformatics in the Department of Epidemiology and Public Health at the University of Maryland School of Medicine are recruiting a full-time, non-tenure track, faculty-level Research Associate with expertise in biostatistics to join a thriving cancer research environment. The successful candidate will be committed to working with Greenebaum Comprehensive Cancer Center members and will hold a primary appointment in the Department of Epidemiology and Public Health.

Applicants must have a Ph.D. or equivalent in Biostatistics, Statistics, Computational Biology, or Mathematics. Primarily, this is a collaborative biostatistics position to help support the research infrastructure of the Cancer Center. This will involve working with a number of different cancer researchers on a range of projects, assisting with experimental design, data analyses, grant development, clinical trials, abstracts and manuscripts.

Preference will be given to experienced individuals who have
1) demonstrated ability to professionally support and manage data analysis projects in collaborative settings across teams of researchers and core services, including grant writing;
2) demonstrated expertise in modern biostatistics, bioinformatics and/or AI methodologies, with cancer-related applications being especially of interest;
3) clinical trial protocol development expertise is a priority but it can be developed, as it will be a required aspect of the position;
4) a record of independent and innovative methodological research would be welcomed and supported as well. In sum, the ideal candidate will have methodological versatility across modern biostatistics and have a strong demonstrated interest and ability to work collaboratively.

Qualified applicants must have a Ph.D. or equivalent in Biostatistics, Statistics, Computer Science, or Applied Mathematics.

Applicants MUST submit an online application at: