Research Staff Scientist

Department

BSD PED - Hematology, Oncology, and Stem Cell Transplantation

The Section of Pediatric Hematology/Oncology provides care for pediatric, adolescent, and young adult patients with cancer and other hematologic diseases, requiring specialty knowledge and skills in Hematology, Oncology, and Stem Cell Transplantation. In addition to patient care, clinical and translational research—including laboratory-based wet lab and dry lab studies—is conducted by faculty members in the section.

The University of Chicago’s Department of Pediatrics, Section of Hematology, Oncology, and Stem Cell Transplantation in the Biological Sciences Division seeks a full‑time Research Staff Scientist to support and advance an interdisciplinary research program focused on life‑course epidemiology, environmental and structural determinants of health, and cancer and reproductive outcomes. The incumbent’s primary activity will be academic research conducted in close collaboration with the Murphy Lab.

The Research Staff Scientist will play a central role in analytic leadership, project coordination, and scientific development across multiple funded studies, including NIH‑funded studies involving complex epidemiologic, clinical, and registry‑linked data. This position is designed for an individual who brings strong quantitative expertise alongside the ability to coordinate scientific workflows, ensure analytic rigor and reproducibility, and contribute substantively to manuscripts, grant applications, and long‑term program development.

The role offers opportunities for intellectual leadership, cross‑institutional collaboration, and sustained involvement in a growing research portfolio.

• Provide analytic leadership for complex epidemiologic, clinical, administrative, and registry‑linked datasets, including development and implementation of analytic plans in collaboration with the Principal Investigator.
• Ensure analytic rigor, reproducibility, and clear documentation of code, workflows, and outputs; support interpretation and visualization of results for manuscripts, presentations, and grant applications.
• Coordinate scientific operations across multiple research projects and grants, managing timelines, milestones, and deliverables in alignment with funded aims.
• Serve as a scientific liaison among team members and collaborators across institutions and disciplines; identify and troubleshoot analytic, scientific, or operational challenges.
• Lead and oversee data governance and regulatory coordination, including DUAs, MOUs, data sharing agreements, and support for IRB submissions and compliance.
• Contribute substantively to grant applications, progress reports, and manuscripts, including methods, analytic plans, preliminary data, and coordination of co‑authors.
• Support strategic development of the research program by identifying opportunities to enhance analytic capacity, data infrastructure, collaborations, and funding.
• Serve as a resource for collecting data and performing analysis; facilitate and promote a research project by providing scientific or intellectual information.
• Train and mentor laboratory personnel.
• Perform other related work as needed.

• PhD in epidemiology, biostatistics, public health, environmental health sciences, data science, or a related field.
• Minimum qualifications:
  
  PhD in a related field; 5–7 years of work experience in a related job discipline.
• Demonstrated experience analyzing complex, large‑scale, or linked datasets.
• Experience navigating data governance and regulatory requirements for human subjects research.
• Strong organizational, project management, and communication skills.
• Ability to work independently while coordinating across multiple projects and collaborators.

• Experience with NIH‑funded research, including multi‑project or center‑style grants.
• Familiarity with registry linkages, administrative data, or high‑resolution omics data.
• Prior experience managing DUAs, MOUs, or data sharing agreements.
• Proficiency in statistical programming languages (e.g., R, SAS, Python).

• Office‑based.

Benefits…