San José State University's Department of Applied Data Science is seeking to expand its interdisciplinary curriculum and research capabilities in areas like Embodied AI, robot perception and control, robotics software systems, multi-modal learning, and Cyber Intelligence with a focus on advanced Machine Learning and AI techniques such as Secure AI. The goal is to prepare students to meet the growing demand for interdisciplinary talent in designing and deploying intelligent, data-driven solutions and to contribute to the department's growth and industry relevance.
Requirements
- expertise in areas such as Embodied AI, robot perception and control, robotics software systems, and multi-modal learning or Cyber Intelligence with a focus on advanced Machine Learning and AI techniques such as Secure AI
- Ability to teach courses in Embodied AI (e.g., multi-modal learning, real-time perception and control, sensor fusion, reinforcement learning, simulation environments) or Trustworthy and Secure AI (e.g., explainable AI, adversarial robustness, privacy-preserving techniques)
- The ability to teach courses to students with diverse academic and professional backgrounds.
- The potential to jointly develop applied research projects in emerging AI and data science fields with Silicon Valley companies.
Responsibilities
- teach courses in areas such as Embodied Artificial Intelligence, Autonomous Systems, Cyber Intelligence, Agentic Cybersecurity with a focus on advanced Machine Learning and AI techniques such as Secure AI and applications of AI in cybersecurity
- engage in collaborative research that addresses real-world challenges involving intelligent agents, autonomous systems, cyber intelligence, and advanced cyber machine learning across various industries and societal domains
- conducting research
- publishing in peer-reviewed journals
- developing grants
- organize all their classes within the Canvas Learning Management System (LMS)
- Ability to teach courses in Embodied AI (e.g., multi-modal learning, real-time perception and control, sensor fusion, reinforcement learning, simulation environments) or Trustworthy and Secure AI (e.g., explainable AI, adversarial robustness, privacy-preserving techniques)
Other
- An earned doctorate in computer science, data science, computer engineering or related fields by the start of appointment.
- Demonstrated potential for scholarly and professional achievement.
- Demonstrated potential for teaching and/or training effectiveness.
- Applicants should demonstrate an awareness of and sensitivity to the educational goals of a socially and economically diverse student population as might have been gained in cross-cultural study, training, teaching, and other comparable experience.
- Industry experience in applied data science, AI, robotics, or related technologies, particularly with Silicon Valley companies or similar innovation ecosystems
