Course Instructor- Generative AI for Engineers

Carnegie Mellon University•Pittsburgh, PA

11h

About The Position

The Department of Mechanical Engineering is looking for an adjunct Instructor to create and teach a course focused on Generative AI for Engineering Applications. This position requires expertise in machine learning, computational modeling, or AI-enabled engineering systems to design and deliver instruction on building, adapting, and applying generative models to mechanical engineering challenges. The role involves core course development, including curriculum design, technical content creation, and assessment development. The curriculum will cover fundamental generative architectures like transformers, diffusion models, and neural operators, with applications in areas such as geometry generation, surrogate modeling, materials and microstructure design, and simulation workflows. The instructor will create practical assignments, guided projects, and assessments utilizing Python, PyTorch, and authentic engineering datasets. Additionally, the instructor will be responsible for recording high-quality asynchronous lecture videos, developing supplementary instructional materials, and ensuring that learning objectives, assessments, and course outcomes are aligned. The instructor will also guide project-based learning and assess student progress through technical assignments and project outcomes. The instructor will deliver all scheduled course sessions according to the Mechanical Engineering academic calendar and fulfill related instructional and administrative tasks. The estimated weekly time commitment for this role is around 10 hours throughout the course duration.

Requirements

Expertise in machine learning, computational modeling, or AI-enabled engineering systems.
Proficiency in Python and PyTorch.
Ability to develop curriculum, technical content, and assessments.
Experience with foundational generative architectures (transformers, diffusion models, neural operators).
Experience applying generative models to engineering problems (geometry generation, surrogate modeling, materials design, simulation workflows).
Ability to record high-quality asynchronous lecture videos.
Ability to develop supporting instructional materials.
Ability to facilitate project-based learning.
Ability to evaluate student performance.
Approximately 10 hours per week commitment.

Nice To Haves

Experience in developing and teaching courses.

Responsibilities

Develop and teach a course on Generative AI for Engineering Applications.
Design and deliver instruction focused on building, adapting, and applying generative models for mechanical engineering problems.
Develop curriculum, technical content, and assessments.
Cover foundational generative architectures such as transformers, diffusion models, and neural operators.
Apply generative models to areas like geometry generation, surrogate modeling, materials and microstructure design, and simulation workflows.
Develop hands-on assignments, guided projects, and assessments using Python and PyTorch and real-world engineering datasets.
Record high-quality asynchronous lecture videos.
Develop supporting instructional materials.
Ensure alignment between learning objectives, assessments, and course outcomes.
Facilitate project-based learning.
Evaluate student performance through technical assignments and project deliverables.
Teach all scheduled sessions listed on the Mechanical Engineering academic calendar.
Complete associated instructional and administrative duties.