Part-Time Lecturer (Solving Complex Problems through Systems Thinking Course)

Tufts Gordon Institute has an opening for a part-time lecturer position at the graduate level to teach EM 207 Solving Complex Problems through Systems Thinking. The part-time lecturer would be teaching an existing course that already has a fully developed curriculum. The course will be taught in person on the Tufts Medford campus during approximately 7 weeks of the second half of the Spring 2027 semester (March-May). Preference is for an individual who is available to teach in a morning time slot that is once a week for a 3 hour duration, but alternative timing selections can be explored.

Based within the School of Engineering at Tufts University, Tufts Gordon Institute provides students with the knowledge and skills they need to lead both teams and entire companies through programs taught by faculty who have excelled in industry. TGI develops leaders by bringing together diverse perspectives to tackle real-world challenges. This cross-disciplinary approach enriches how we teach applied business-where technical expertise meets strategic thinking meets human insight.

Course Overview

Barry Richmond is credited with coining the phrase "Systems Thinking" in 1994; his paper provided a crisp definition:

"Systems Thinking is the art and science of making reliable inferences about behavior by developing an increasingly deep understanding of underlying structure"

[1] System Dynamics/Systems Thinking: Let's Just Get On With It, Richmond, B. , 1994 International Systems Dynamics Conference

EM 207 focuses on building models of individual systems, and systems-of-systems, from data about their behavior. These models use a few, simple structural concepts, and define "systems" as entities that:

• Have measurable attributes
• May have stocks, inventories, or collections of resources
• Perform functions/actions, such as:
  
  
  
  • responding to inputs
  • producing outputs
  • producing and receiving flows
  
  
  
  
• Have modes or "states" of behavior
• May contain other systems

Course Topics

EM207 uses a variety of tools to collect, analyze, and model behavioral data:

* Object-oriented analysis to build system ontologies

* Stock and flow modeling with time-slice models

* Regression analysis to model transfer equations

* State-machine analysis

* Designed experiments for building transfer equations

* Control loops for harnessing and managing feedback

The end goal is to "explain" past behavior, and predict future behavior, enabling the design of modifications to produce desired effects.

The ideal candidate has professional experience in program management, business development and creative problem solving. An advanced STEM degree is strongly recommended.

Candidates should submit their application, including a cover letter and resume through Interfolio. Candidates are encouraged to demonstrate attention to diversity and inclusion as it relates to teaching, research, and scholarship throughout their application.