The NSF CREST Center at Texas State University is seeking to establish a leading research position in ultrawide bandgap (UWBG) semiconductor materials and education. This involves developing advanced AI models for UWBG semiconductor processes to enable next-generation devices for high power, high frequency, and extreme condition applications.
Requirements
- hands-on experience in the development of machine learning and deep learning modeling and analysis
- utilization of containers
- understanding data analytics modeling
- Experience in Reinforcement Learning (not mandatory but preferred)
- Ph.D. in ECE, CS, or another related field by the time of appointment
- demonstrated a strong publication record in applied AI development
Responsibilities
- application and development of AI modeling in ultra-wide bandgap (UWBG) semiconductor processes
- development of machine learning and deep learning modeling and analysis
- utilization of containers
- understanding data analytics modeling
- implement new fabrication, processing, and doping strategies to produce novel UWBG heterointerfaces
- develop new scanning probe microscopy-based UWBG characterization techniques to interrogate UWBG heterointerfaces
- develop UWBG material-aware AI-based models to investigate materials and heterostructures
Other
- Highly self-motivated and proactive, with exemplary scientific problem-solving skills
- Demonstrated ability to work independently as well as with teams
- Motivated to produce publications and write research proposals
- Motivated to mentor students
- Email your CV and cover letter to dvalles@txstate.edu
