This position is grant-funded. We anticipate this to be a 12-month, benefits-eligible term appointment, dependent on the needs of the department. The position duration is renewable for up to 2 years, depending on performance, department needs, and availability of funds.JOB SUMMARYThe research engineer will support the Department's research on advancing Microelectronic Devices Design and Manufacturing. This includes semiconductors, system-on-chip, heterogeneous integration/advanced packaging and trusted artificial intelligence.
ESSENTIAL FUNCTIONS- Develop innovative solutions and technical approaches to design, modeling, and implementation of advanced AI models for microelectronics design and manufacturing.
- Create a digital twin of the current and planned microelectronic device and manufacturing systems on the digital twin.
- Serve as lead author on project reports, journal articles, conference papers, and presentations.
- Develop experimental test plans to validate models from real-world sensor data.
- Leads and supports technical proposals for developing new projects.
- Meet grant goals and deliverables by completing assigned research tasks and reports.
- Supervise and lead student researchers (undergraduate and graduate).
- Work closely with the faculty and project team. Contributes to the overall success of the project by performing other essential duties and responsibilities as assigned.
QUALIFICATIONSMinimum Qualifications- Completed a Master's degree (U.S.) in Electrical and Computer Engineering.
- Proven expertise in developing complex AI models with applications to visual data processing.
- Demonstrated publication record
- Proven communication, time management, and teamwork skills
- This project is funded by the Department of Defense. Export control laws define a U.S. person as a U.S. citizen.
An equivalent combination of education and experience from which comparable knowledge and skills have been acquired may be substituted.
Preferred Qualifications- Experience with developing secure Vision-based AI models, robot control, motor control and ROS2.
- Experience in developing digital twin models
- Experience in advanced robot controls, such as nonlinear methods and data-driven techniques.
HOW TO APPLYAll interested candidates must apply online at https://www.stthomas.edu/jobs/. Follow the instructions to complete an online application which includes creating or updating an applicant profile, uploading a resume, and completing a job specific application.
In light of its commitment to create and maintain a safe learning and working environment, employment with the University of St. Thomas requires consent and successful completion of a background screening.
Official job posting is available at www.stthomas.edu/jobs.
