Adjunct, Data Science

Monmouth University is seeking qualified candidates for an Adjunct Professor of Data Science in the Computer Science and Software Engineering department. The successful candidate will teach undergraduate and/or graduate-level courses in Data Science.

Part-time adjunct faculty members typically teach 3-6 credits per semester, with class schedules determined based on departmental needs and candidate availability. Courses are taught in person at the West Long Branch campus. Adjunct positions remain posted continuously to expand the university’s pool of qualified adjunct faculty. Screening of applications will commence when an open position becomes available. Should a position become available, you will receive an email advising you of the next steps.

This is an in-person, on-campus, non-remote position.

For additional information about the department, please visit the Department of Computer Science and Software Engineering webpage.

Additional Application Material Required:

Monmouth University requires all applications and supporting documents to be submitted via the university’s career portal. In addition to the application, candidates must upload the following documents. Applications will not be considered complete for review until all required documents are uploaded.

• Resume or Curriculum Vitae

• Cover Letter

• Contact Information for Three Professional References

• Two Letters of Recommendation

Optional Documents: Additional materials such as evidence of teaching effectiveness or student mentoring.

Special Instructions to Applicants:

We encourage candidates to include information in the cover letter that addresses their approach to teaching and their plans to advance diversity, equity, and inclusion in their position at Monmouth University.

Duties and Responsibilities:

• Teach 3-6 credits of undergraduate and/or graduate-level Data Science courses each semester, including topics such as data analytics, machine learning, ethics and bias in AI, applications of data science, advanced data science techniques, natural language processing, deep learning, computer vision, and low-code/no-code data analysis.

• Develop and deliver course lectures, discussions and assignments in accordance with the curriculum and learning objectives.

• Provide time during the week to meet with students outside of class.

• Foster a positive and inclusive learning environment conducive to student engagement and academic success.

• Develop and administer projects and exams to evaluate student learning outcomes and provide grades in a timely manner.