Adjunct Instructor in Generative AI in Clinical Decision Support at Brandeis University

Waltham, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

22 Aug, 26

Salary

6573.15

Posted On

24 May, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Generative AI, Clinical Decision Support, Large Language Models, Prompt Engineering, Python, R, Online Instruction, Moodle, Health Informatics, Curriculum Facilitation, Academic Discourse, Rubric-based Evaluation, Data Science, AI Safety, Regulatory Compliance, Culturally Responsive Pedagogy

Industry

Higher Education

Description

Brandeis University’s Online Health Informatics Program is seeking an Adjunct Faculty member for RHIN 175 Generative AI in Clinical Decision Support for the Fall-2 2026 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Health Informatics. This course includes an examination of Large Language Models (LLMs) and generative artificial intelligence (AI) for clinical support: pilot design, prompt engineering, validation, safety, monitoring, and regulatory considerations. The course will also teach students how to assess deployment and impacts of AI in clinical workflows. 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 or Ph.D.) in Computer Science, Health Informatics, Data Science, Engineering, or a related field Strong knowledge of AI fundamentals and its application to healthcare in addition to a strong grasp of the ethical implications of its usage Minimum of 3 years of professional experience in developing and deploying real-world AI solutions Proficiency in a programming language (e.g. Python, R) 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 Knowledge of global learner personas and culturally responsive pedagogy Familiarity with Moodle LMS and digital authoring tools (e.g., H5P) 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 June 1, 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 positon 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"). COME WORK WITH US Brandeis University is a great employer for all the same reasons it is an outstanding university. Its commitment to inclusion, dedication to lifelong learning and commitment to excellence are just a few of the reasons our workplace culture shines bright. We take pride not only in maintaining this culture, but expanding it — by recruiting and retaining outstanding employees who share our values and enrich Brandeis University overall. 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, military or veteran status or any other category protected by law (also known as membership in a "protected class"). Applicants who require accommodation in the job application process are welcome to contact Human Resources at 781-736-4474 or via email, humanresources@brandeis.edu. The health and safety of the Brandeis community is important. While not required, we strongly recommend that employees are fully vaccinated. For additional information feel free to review the Human Resources Office website. Certain positions at Brandeis University may require a background check. To review this policy, visit our website at http://www.brandeis.edu/human-resources/onboarding/index.html

Responsibilities

The instructor will facilitate an asynchronous online course on Generative AI in Clinical Decision Support, managing course logistics and student engagement. Responsibilities include hosting introductory sessions, facilitating academic forums, and providing rubric-based grading and feedback.