Limited Term Adjunct Lecturer

Tucson, AZ
Jun 02, 2021
Position Type
Employment Type
Part Time
Institution Type
Four-Year Institution
Posting Number:



Nutritional Sciences-Ins

Department Website Link:

Medical Sub-Speciality:


Main Campus


Tucson, AZ USA

Position Highlights:

The mission of the Department of Nutritional Sciences (NSC), College of Agriculture and Life Sciences at the University of Arizona, is to lead in providing cutting-edge Research, outstanding Undergraduate and Graduate Programs, and Cooperative Extension activities that advance the discovery and translation of the roles of nutrition in optimizing health for people in Arizona, the nation, and the world. NSC takes a collaborative and interdisciplinary approach in discovering, integrating, extending, and applying knowledge of nutritional science to promote optimal nutritional status, health, and wellbeing, and to prevent and to treat chronic diseases including cancers, diabetes, obesity, heart disease and musculoskeletal disorders.
The Department of Nutritional Sciences is seeking a limited term adjunct lecturer for Fall semester of 2021. Applicants should have a broad knowledge of research design, data management and data analysis.
The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

Duties & Responsibilities:

This position is part-time, 100% instruction, assigned two courses in the fall 2021 semester. Teaching responsibilities include:
-Teach Introduction to Methods for Research in Nutritional Science and Applied Statistical Methods for Research in Nutritional Science. NSC 501 for Introduction to Methods for Research in Nutritional Science and NSC 502 for Applied Statistical Methods for Research in Nutritional Science
-Develop and/or revise course materials as needed.
-Deliver courses online to graduate and professional students.

Minimum Qualifications:

MS in biostatistics, statistical analysis, data science, mathematics, or related area

Preferred Qualifications:

- PhD in biostatistics, statistical analysis, data science, mathematics or related area
- College-level teaching experience including in-person and online.
- Experience with course management systems such as Desire2Learn

Rank :


Tenure Information:

Adjunct (NTE)



Full Time/Part Time:

Part Time

Number of Hours Worked per Week:


Job FTE:


Work Calendar:


Job Category:


Benefits Eligible:

No Benefits

Rate of Pay:


Compensation Type:

Per Course

Type of criminal background check required::

Name-based criminal background check (non-security sensitive)

Number of Vacancies:


Target Hire Date:

Expected End Date:

Contact Information for Candidates:

Scott Going
[email protected]

Open Date:


Open Until Filled:


Documents Needed to Apply:

Curriculum Vitae (CV) and Cover Letter

Special Instructions to Applicant:

Diversity Statement:

At the University of Arizona, we value our inclusive climate because we know that diversity in experiences and perspectives is vital to advancing innovation, critical thinking, solving complex problems, and creating an inclusive academic community. As an Hispanic-serving institution and a Native American/Alaska Native-serving institution, we translate these values into action by seeking individuals who have experience and expertise working with diverse students, colleagues, and constituencies. Because we seek a workforce with a wide range of perspectives and experiences, we provide equal employment opportunities to applicants and employees without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity, or genetic information. As an Employer of National Service, we also welcome alumni of AmeriCorps, Peace Corps, and other national service programs and others who will help us advance our Inclusive Excellence initiative aimed at creating a university that values student, staff and faculty engagement in addressing issues of diversity and inclusiveness.

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