Adjunct Instructor in Assessment, Selection, and Employment Law
Brandeis University’s Online Industrial Organizational Psychology Program is seeking an Adjunct Faculty member for RIOP 115 Assessment, Selection, and Employment Law for the Fall 1 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Industrial Organizational Psychology.
The course will integrate applied study of job analysis, assessment design, structured interviews, validation strategies, and the legal framework governing employment decisions, including adverse‑impact considerations that will enable students to design defensible selection systems.
Core Course Responsibilities Summary
Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.
Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.
Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.
Qualifications:
Required:
Advanced degree (Master’s, Ph.D., PsyD, or J.D.) in Industrial-Organizational Psychology, Psychometrics, Statistics, Applied Psychology or Human Resource Management (with a quantitative focus), Behavioral Science, Data Science, Employment Law or a related field.
Minimum 2 years professional experience within diverse industries or sectors, with a focus on HR/people/workforce analytics, psychometrics, HR business partnering or strategy development (with quantitative focus), talent management (with quantitative focus), personnel or workplace research, applied data science, employment law or related roles.
Strong knowledge of methods used for designing legally defensible selection systems grounded in job analysis and validation, identifying and mitigating adverse impact and legal risks in selection procedures, implementing structured assessment batteries and evaluating operational effectiveness of assessment and selection systems.
At least 1 year of teaching or training experience (preferably online/asynchronous)
Experience with online instruction
Excellent communication and teaching skills in an online learning environment.
Preferred:
Prior online teaching experience at the graduate level
Familiarity with online education platforms and course development tools.
Interested candidates should submit:
A cover letter highlighting relevant qualifications and teaching experience.
A current CV or resume.
Contact information for three professional references.
Application review begins 5/28/2026 though we will continue to accept submissions on an ongoing basis.
This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.
Compensation for this position is $6573.15
Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").
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The course will integrate applied study of job analysis, assessment design, structured interviews, validation strategies, and the legal framework governing employment decisions, including adverse‑impact considerations that will enable students to design defensible selection systems.
Core Course Responsibilities Summary
Course Logistics and Facilitation: Focuses on the organized and timely rollout of course content, maintaining consistent communication through weekly announcements, and ensuring all instructional activities occur within university-approved digital platforms.
Instructor Presence and Engagement: Centers on building an active teaching persona by hosting live introductory sessions, facilitating weekly academic discourse in forums, and maintaining regular availability for student consultation.
Individual Feedback and Grading: Emphasizes the professional obligation to provide transparent, rubric-based evaluations and supportive commentary on student work within a standardized weekly timeframe.
Professional Conduct and Standards: Requires adherence to university communication protocols, the promotion of respectful online "netiquette," and ensuring the course meets accessibility and technical visibility standards before and during the term.
Qualifications:
Required:
Advanced degree (Master’s, Ph.D., PsyD, or J.D.) in Industrial-Organizational Psychology, Psychometrics, Statistics, Applied Psychology or Human Resource Management (with a quantitative focus), Behavioral Science, Data Science, Employment Law or a related field.
Minimum 2 years professional experience within diverse industries or sectors, with a focus on HR/people/workforce analytics, psychometrics, HR business partnering or strategy development (with quantitative focus), talent management (with quantitative focus), personnel or workplace research, applied data science, employment law or related roles.
Strong knowledge of methods used for designing legally defensible selection systems grounded in job analysis and validation, identifying and mitigating adverse impact and legal risks in selection procedures, implementing structured assessment batteries and evaluating operational effectiveness of assessment and selection systems.
At least 1 year of teaching or training experience (preferably online/asynchronous)
Experience with online instruction
Excellent communication and teaching skills in an online learning environment.
Preferred:
Prior online teaching experience at the graduate level
Familiarity with online education platforms and course development tools.
Interested candidates should submit:
A cover letter highlighting relevant qualifications and teaching experience.
A current CV or resume.
Contact information for three professional references.
Application review begins 5/28/2026 though we will continue to accept submissions on an ongoing basis.
This appointment is to a position that is in a collective bargaining unit represented by SEIU Local 509.
Compensation for this position is $6573.15
Pay Range Disclosure
The University's pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience and education/training, internal peer equity, and applicable legal requirements.
Equal Opportunity Statement
Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race, color, ancestry, religious creed, gender identity and expression, national or ethnic origin, sex, sexual orientation, pregnancy, age, genetic information, disability, caste, military or veteran status or any other category protected by law (also known as membership in a "protected class").
Apply To This Job