Department: Dean, Engineering

Salary: Commensurate with experience

Description:

The Department of Mechanical Engineering at the University of Houston invites applications for a part-time Lecturer position focused on teaching graduate-level courses in data sciences, artificial intelligence and machine learning as part of the Master’s and Certificate program in Engineering Data Science offered by the Cullen College of Engineering.

The candidate will be expected to teach one or two courses in a semester. Interest and expertise in teaching courses such as the following is desirable. - Introduction to Data Science - Machine Learning - Data Mining - Artificial Intelligence - Cloud Computing Engineering Data Science is a broad field that encompasses predictive modeling and data-driven design of engineering systems. The demand for graduates with a data science background is already high and is growing rapidly across a wide range of industries worldwide.

Houston, being the energy capital of the world as well as the home of a thriving healthcare industry, is also seeing a persistent demand for workforce well-trained in data science. To provide state-of-the-art training for a data-centric workforce, the Cullen College of Engineering offers a Master of Science in Engineering Data Science. A post-graduate Certificate in Engineering Data Science is also offered to cater to working professionals interested in developing expertise in data science. For more information about the programs, please visit: https://researchcomputing.egr.uh.edu/academic-programs/master-science-engineering-data-science

As part of a major drive for excellence, including the designation of UH as a Carnegie Tier One Research university, the Cullen College of Engineering has a strong commitment to expand, as well as, advance the quality of our engineering research programs. UH is Texas’ premier public metropolitan research and teaching institution with more than 40,000 students. Houston is home to the Texas Medical Center, the largest medical center in the world, the NASA Johnson Space Center, and multiple high-tech companies offering excellent local collaboration opportunities.

Qualifications
The preferred candidate will have a graduate degree in a relevant area of physical sciences, engineering, data science or related discipline with research or professional experience in the specific subject area(s) to be taught.