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Brandeis University

Adjunct Instructor in Software Development in Python

Posted 2 days ago
$6573.15 per year
2-5 years experience
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AI Summary

The instructor is responsible for facilitating an asynchronous online course, including content rollout, student communication, and forum engagement. They must also provide transparent, rubric-based grading and maintain university standards for accessibility and professional conduct.

Brandeis University’s Rabb School is seeking an Adjunct Faculty member for RSEG 111: Software Development in Python, for the 2027 Spring 1 session. This 3-credit asynchronous online course is an 8-week requirement for the Master of Science in Software Engineering Software Engineering Artificial Intelligence Track and Software Engineering with Artificial Intelligence Online Master's Certificate.


Course Description: This course involves software development, scientific problem-solving and machine learning approaches using Python. Topics include procedures and functions, iteration, recursion, arrays and vectors, strings, an operational model of procedure and function calls, algorithms, exceptions, object-oriented programming, and GUIs (graphical user interfaces). Students will practice scientific programming and machine learning approaches using libraries such as SciPy, NumPy, Keras or Pytorch.


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:
    • Master’s degree (Doctorate preferred) in Computer Science or in a relevant discipline
    • At least 1 year of teaching or training experience (preferably online/asynchronous)
    • Proficiency with LMS platforms and digital authoring tools
    • Familiarity with analytical tools, collaborative platforms, and interdisciplinary teamwork
    • Strong communication, organization, and independent work skills
  • Preferred:
    • Experience teaching or developing graduate-level online courses
    • 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)

Application Process: 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 October 29, 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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