Assistant Researcher

The Department of Public Health and Community Medicine is an academic department within the Tufts University School of Medicine located on the Health Sciences Campus in Boston. Technical and academic assets within the department provide a strong research support system for federally-funded research. Its 35 full-time faculty members hold advanced degrees in epidemiology, biostatistics, sociology, anthropology, law, medicine, nutrition, biology, engineering, health policy, economics, social policy, education, social work, and the behavioral sciences. Department research includes a focus on the following thematic areas: health equity, substance use disorders, health communication, nutrition and infection, infectious disease epidemiology, health policy and health care delivery, environmental health, the opioid epidemic, and global health. Department faculty are methodologically strong and diverse, with expertise in biostatistics, survey research, program evaluation, qualitative methods, dietary assessment, and spatial epidemiological analysis.

Substance use disorder (SUD) presents major public health challenges in the State of Idaho. Opioid, stimulant, and alcohol vulnerability assessments are needed to identify locations in need of targeted prevention and treatment responses. A Tufts University School of Medicine team, led by Drs. Stopka and Shrestha, has been contracted by the State of Idaho to conduct these vulnerability assessments employing GIS, spatial epidemiological, and statistical analyses.

Under the supervision of the Tufts MPIs (Drs. Stopka and Shrestha), provides specialized subject matter knowledge to develop, implement, coordinate, and evaluate a research study in collaboration with the Tufts, Idaho, and Massachusetts public health experts. Develops goals and strategies; designs data management and reporting systems; manages program/project financial, operational, and human resources; contributes to development of grant proposals for continued or new funding. This individual will conduct research, help to oversee study team logistics, meetings, and activities, develop progress reports, and assist with dissemination of findings through presentations at public health meetings, scientific conferences, and peer reviewed journal articles. This individual will also provide support to study team members at Tufts and Boston Universities, as well as the Idaho, Massachusetts, and Lowell, Massachusetts public health departments. This individual will assist with data analyses focused on opioid, stimulant, and alcohol vulnerability analyses in Idaho, as well as overdose-related analyses across Massachusetts and on the local level for Lowell, Massachusetts.

The goals and objectives are:

1) To conduct Idaho vulnerability assessments for alcohol and stimulants and update the opioid vulnerability assessment presented in January 2021;

2) Produce a report of vulnerability assessment project findings, which includes how the findings can be used to address service gaps as well as recommendations for targeted intervention considerations based on the assessment findings.

In addition, opioid overdose deaths continue to present major public health challenges in Massachusetts. Through the Massachusetts HEALing Communities and the STOP OD Lowell studies, we are conducting spatial and statistical analyses, and developing opioid-related overdose prediction models to better understand and target local overdose prevention needs.

Basic Requirements:

• The following required knowledge and skills as typically acquired by completing a Bachelor’s degree in related discipline and 2+ years research experience
• Research and data management skills
• Proficiency with statistical software

Preferred Qualifications:

• MPH of master’s degree in the social sciences
• Basic/Intermediate experience with statistical and spatial analysis software (e.g., SAS, R, ArcGIS, SatScan)
• Experience working with community members with opioid use disorder (OUD)
• Experience working with ACASI, REDCap, and Qualtrics programs desirable
• Experience with multilevel statistical modeling desirable
• Advanced statistical coding experience in SAS and R desirable