Staff Scientist

Department

BSD MED - Hematology and Oncology - Izumchenko Research Staff

About the Department

We are aiming to recruit a skilled Staff Scientist to the Translational Head and Neck Cancer Research group led by Drs. Evgeny Izumchenko and Nishant Agrawal. Our focus is on understanding the complex interplay between the genetic and epigenetic alterations in head and neck carcinogenesis and progression, and on exploiting this understanding for developing novel biomarkers for diagnosis and risk stratification as well as in identifying targets for therapeutic intervention. Drs. Izumchenko and Agrawal lab is an integral component of the translational head and neck cancer research program at the University of Chicago, working collaboratively with the team of investigators with complementary and integrated expertise including surgeons, clinical oncologists, pathologists and computational biologists. Our group members are known for their contributions to the advancement of groundbreaking research, pursuing a diverse range of basic, translational, and clinical research projects on head and neck cancer genetics, microbiome, bioengineering, stem cell renewal, and immunotolerance.

Job Summary

The Staff Scientist will design, plan and perform a variety of complex and technical experiments using both cellular and animal models in support of clinical and translational research studies conducted by principal investigators (PIs) for the research program to ensure adherence to clinical and experimental protocols and the quality of information received. In addition, the candidate will be responsible for data analysis, training new staff, managing research data, write manuscripts and assist with grant preparation and project management.

Responsibilities

• Develop and design complex, hypothesis-driven experiments aligned with lab goals.

• Independently conduct molecular, cellular, and in vivo experiments (e.g., cell culture, flow cytometry, animal models, CRISPR, omics technologies).

• Implement state-of-the-art techniques in cancer biology, including genomics, transcriptomics, proteomics, and imaging.

• Troubleshoot technical issues and optimize protocols.

• Analyze large datasets from high-throughput experiments.

• Perform statistical analysis and bioinformatics relevant to cancer research.

• Interpret findings in the context of current scientific literature and cancer biology.

• Identify novel biomarkers, drug targets, or mechanistic insights.

• Lead multiple research projects simultaneously with minimal supervision.

• Manage timelines, resources, and milestones effectively.

• Coordinate collaborations with internal teams and external academic or industry partners.

• Supervise and mentor junior staff, technicians, graduate students, or postdocs.

• Prepare manuscripts for peer-reviewed publications.

• Contribute to grant writing, progress reports, and funding proposals.

• Maintain detailed and accurate lab notebooks and documentation for reproducibility.

• Serves as a resource for collecting data and performing analysis. Facilitates and promotes a research project by providing scientific or intellectual information.

• Creates first drafts for scientific writing and publications, including protocols and grants.

• Performs other related work as needed.

Minimum Qualifications

Education:

Minimum requirements include a PhD in related field.

Work Experience:

Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline.

Certifications:

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Preferred Qualifications

Experience:

• Experience working in Translational/Clinical research settings.

• Experience facilitating and promoting a research project or contributing to the scientific direction of a research resource (core facility).

Preferred Competencies

• Deep knowledge of cancer biology, including molecular pathways, tumor microenvironment, metastasis, and therapy resistance.

• Familiarity with cancer models: xenografts, syngeneic models, PDX models, genetically engineered mouse models.

• Knowledge of statistical methods and experimental design.

• Ability to formulate hypotheses.

• Ability to interpret omics datasets.

• Strong writing skills.

• Works effectively with multidisciplinary teams.

Application Documents

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