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The Suffolk University McNair Scholars Program invites applications for a Quantitative Reasoning Instructor for Spring 2026. This position is designed to strengthen scholars' academic skills for success in graduate-level study. In accordance with 34 CFR 647.30(a), this time-limited role constitutes "activities of an academic or scholarly nature ... which have as their purpose the encouragement and preparation of project participants for doctoral studies." The McNair Scholars program supports first-generation and income-eligible college students who have demonstrated a commitment to preparing for and pursuing research doctorates.

Appointment:February - March/April 2026 (8 weeks)
Schedule: ~2-hour, in-person, class session per week; evenings, class time to be determined in conjunction with McNair program director; no classes week of March 9th due to Spring Break
Type:Time-limited, seasonal instructor

Pay: $3,000, flat-rate, per course, paid bi-weekly in accordance with the University pay schedule

This position is grant funded by the U.S. Department of Education's McNair Scholars Program Award # P217A220037 at Suffolk University

Responsibilities

The Quantitative Reasoning instructor will lead an eight-week, in-person, academic class series that enhances mathematical reasoning, analytical precision, and problem-solving for graduate-level readiness. Core topics may include:

• Algebraic expressions, equations, and inequalities
• Functions and coordinate geometry
• Data interpretation, statistical reasoning, and proportional analysis
• Arithmetic and number properties
• Quantitative comparison and applied logic

The Quantitative Reasoning Instructor will be expected to:

• Design and facilitate weekly two-hour classes emphasizing conceptual understanding and applied reasoning.
• Integrate analytical exercises that mirror graduate-level expectations without functioning as commercial test-preparation instruction.
• Connect quantitative reasoning to research design, data analysis, and doctoral-level inquiry.
• Provide brief formative assessments and individualized feedback to track progress.
• Offer limited individual or small-group tutoring sessions, by appointment, to reinforce class material and address specific learning needs.
• Coordinate with McNair staff on instructional planning, attendance documentation, and content summaries for grant reporting.

Combined Appointment Option

The McNair Program is looking for instructors in both quantitative reasoning and verbal and analytical-writing instruction. Applicants with demonstrated expertise inbothquantitative reasoningandverbal or analytical-writing instruction may be considered for appointment toboth instructional tracksduring the same spring term. If you are interested in being considered for both, you may submit all materials to the one job posting that would be your preferred subject, but please make your interest and qualifications for both positions explicit in your cover letter.

Qualifications

• Bachelor's degree required; master's degree or higher preferredin a relevant discipline
• Demonstrated experience teaching or tutoring college-level students in the relevant content area.
• Proven ability to design engaging, scaffolded instruction that develops academic and analytical skills necessary for graduate study.
• Commitment to equity-minded pedagogy and mentorship of first-generation and low-income scholars.
• Familiarity with graduate-level academic expectations preferred.
• Familiarity with and/or working with federal TRIO program populations preferred

Applications should be made through the Suffolk HR website, with a complete submission including the following components: (1) CV/Resume; (2) Cover Letter detailing the rationale for applying to the role and relevant qualifications; (3) Recent Teaching Evaluations (if available). Applications without cover letters will NOT be considered. If candidate is a finalist, three professional references will be required before a final offer is made. Review of applications will begin immediately.

Salary:$3,000.00 per course