The posting
Job Description
Working independently but in close cooperation and in consultation with the Principal Investigator and other Research Scientists, the Postdoctoral Scientist will perform routine and complex laboratory procedures throughout training period. May develop, adapt, and implement new research techniques and protocols.
Analyzes and interprets data. May assist in preparation of grant proposals. Participates in publications and presentations as author or co-author. Not responsible for generating grant funds.
As a Postdoctoral Scientist, you will be a vital member of Dr. Tan’s interdisciplinary research team, which includes biostatisticians, qualitative research specialists, and grant administration and project management professionals. Responsibilities include leading quantitative and qualitative research projects, supporting participant engagement efforts, and fostering strong partnerships with community stakeholders and collaborators.
This role follows a hybrid work schedule; however, we can only consider applicants who will be able to commute to our Los Angeles work location a few times per week. If hired you must reside in the commutable area.
The Postdoctoral Scholar will lead advanced quantitative analyses using dyadic and multilevel modeling approaches to support innovative cancer prevention and control research within the Tan Lab at Cedars-Sinai. This role focuses on addressing health disparities and advancing research initiatives related to lung cancer survivorship, prostate cancer shared decision making, smoking cessation, and pancreatic cancer intervention development. Working closely with the Principal Investigator, the scholar will contribute to high-impact publications, grant-supported research activities, and the development of evidence-based interventions that improve patient outcomes across diverse populations.
Primary Duties and Responsibilities
- Establish and maintain lab and study-specific SOP
- Provides timely and constructive feedback to study team.
- Delegate responsibilities to team members to efficiently execute research protocols and procedures.
- Experience working in interdisciplinary and transdisciplinary teams.
- May assist in the preparation of grant proposals, but is not responsible for generating grant funds.
- May participate in publications and presentations as author or co-author.
- Designs and performs experiments. Will keep appropriate experimental records and documentation and analyze the results with the Principal Investigator (PI).
- May develop, adapt, and implement new research techniques and protocols.
- Analyzes interpret, summarizes, and compiles data.
- Performs routine and complex laboratory procedures throughout the training period.
- Operates and maintains equipment and instruments.
- May observe PI-patient or PI-human research subject interactions as it pertains directly to research being performed.
Day-to-Day Responsibilities
- Lead and conduct advanced statistical analyses utilizing dyadic matched-pairs and multilevel modeling methodologies for cancer prevention and control research studies.
- Collaborate with the Principal Investigator and research team to support study design, protocol development, and interpretation of complex research findings.
- Analyze hierarchical and interdependent data structures to address health disparities and inform intervention development.
- Support ongoing research initiatives related to lung cancer survivorship, prostate cancer shared decision making, smoking cessation, and pancreatic cancer interventions.
- Prepare manuscripts, abstracts, presentations, and other scholarly materials for publication and scientific dissemination.
- Contribute to grant proposal preparation and other research-related funding activities.
- Maintain organized research workflows, support laboratory operations, and ensure timely execution of project deliverables.
- Participate in interdisciplinary collaboration with faculty, clinicians, and research staff to advance the Cancer Center’s research mission.
Qualifications
This role follows a hybrid work schedule; however, we can only consider applicants who will be able to commute to our Los Angeles work location a few times per week. If hired you must reside in the commutable area.
Requirements:
- Doctorate (MD, PhD, VMD, or DDS) in area directly related to field of research specialization.
- Only applicants who submit a cover letter with their application materials will be considered for this opportunity. In your cover letter, please describe one project in which you analyzed dyadic data. Include the study design, the source of non-independence within the data, the approach used to model that interdependence, and the statistical software used.
- 1 year, acquires thorough technical and theoretical knowledge of research project and objectives during one to five (1-5) year post-doctoral appointment.
- Demonstrated experience independently analyzing dyadic or other non-independent paired data, where observations are nested within pairs (e.g., romantic couples, parent–child, patient–provider, roommate, or sender–receiver pairs).
- Experience directly modeling interdependence between partners, using approaches such as the Actor–Partner Interdependence Model (APIM), dyadic multilevel/mixed-effects models, the Social Relations Model, common-fate models, or dyadic structural equation models.
- Evidence of prior independent dyadic data analysis through publications, preprints, a dissertation chapter, or shared analysis code.
- Please note: Individual-level analyses that include a partner characteristic solely as a covariate do not meet this qualification.
Preferred:
- Experience analyzing distinguishable and/or indistinguishable dyads.
- Experience with dyadic longitudinal or daily-diary study designs.
- Experience conducting power analyses for dyadic models.
- Demonstrated expertise in dyadic data analysis, matched-pairs research design, and multilevel modeling techniques.
- Experience conducting quantitative research in cancer prevention, survivorship, behavioral interventions, or health disparities research.
- Strong proficiency with statistical software packages such as R, SAS, SPSS, Stata, or Mplus.
- Proven track record of scholarly productivity, including peer-reviewed publications and scientific presentations.
- Experience supporting or contributing to grant-funded research activities and manuscript development.
- Strong analytical, organizational, and communication skills with the ability to manage multiple research priorities in a collaborative academic environment.
- Ability to work independently while contributing effectively within a multidisciplinary research team.
