Postdoctoral Scholar Research Associate

The Department of Population and Public Health Sciences at the Keck School of Medicine seeks a passionate and committed Postdoctoral Scholar Research Associate to join a dynamic, interdisciplinary team engaged in translational environmental health research. Our NIH-funded projects span environmental and molecular epidemiology, computational toxicology employing artificial intelligence, experimental studies (in vitro and in vivo), and advanced multiomics data science. We are looking for candidates with expertise or interest in environmental health, biostatistics, and data science, especially as applied to environmental chemical exposures, type 2 diabetes, kidney disease, liver cancer, and renal cancer. 

The ideal candidate will be open-minded, eager to learn, and enthusiastic about engaging in our multidisciplinary research efforts. Key responsibilities for this role include:

• Initiating, planning, and overseeing research projects
• Leading the analysis of complex multiomics data, including single-cell and spatial omics, using R or Python; experience with these datasets is helpful but not required
• Preparing statistical reports and presentations
• Presenting findings at regional or national scientific meetings
• Mentoring or overseeing biostatisticians and graduate students
• Contributing to the writing of scientific manuscripts and grant proposals
• Collaborating with team members on cross-disciplinary research projects.
• Keeping abreast of the latest research methodologies and participating in relevant training sessions and conferences

Minimum qualifications required for this position include:

A doctoral degree (Ph.D., MD, DO, DVM, PharmD) in Environmental Health, Epidemiology, Biostatistics, or closely related fields. Demonstrated ability to manage multiple projects simultaneously. Strong scientific writing and oral communication skills. Strong analytical and problem-solving skills. Intermediate to advanced coding skills in R or Python. The ability to collaborate effectively with a diverse team.

Preferred qualifications include:

• Experience in analyzing large biological datasets (e.g., scRNAseq, metabolomics, proteomics)
• Proficiency in collaborative coding environments (e.g., git/GitHub)

This role presents significant opportunities for professional development and growth. Given the interdisciplinary nature of our work, we encourage applications from candidates with a broad range of academic backgrounds.

The annual base salary range for this position is $62,400 - $70,000. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate’s work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.

JOB QUALIFICATIONS: Minimum Education: Ph.D. or equivalent doctorate within previous five years Minimum Experience: 0-1 year Minimum Field of Expertise: Directly related education in research specialization with advanced knowledge of equipment, procedures and analysis methods. Preferred Field of Expertise: Publications in peer-reviewed journals in the same or related field. Skills: Other: Analysis Assessment/evaluation Communication -- written and oral skills Conceptualization and design Organization Planning Problem identification and resolution Project management Research Statistical analysis Skills: Machine/Equipment: Calculator Computer network (department or school) Computer network (university) Computer peripheral equipment Fax Personal computer Photocopier Supervises: Level: May oversee student, temporary and/or casual workers. Comments: A copy of the doctoral diploma or other certification that indicates that the terminal degree has been completed satisfactorily is required. If the doctoral candidate has not yet obtained a degree, he/she should provide evidence that a thesis has been approved together with a documented indication of the expected date of formal graduation. It is the responsibility of the faculty mentor to verify this documentation. The documentation is to be filed with the Office of Postdoctoral Affairs.