A Postdoctoral Scholar position in the areas of neurophysiological signals & human-autonomy teaming is available at University of California, Davis, for working on an AFOSR-funded project. In future military and civilian settings, humans will interact with ever-more autonomous technical systems. Due to the safety- and mission-critical nature of many such systems, human mistrust, distrust, over reliance, or skepticism of autonomy may lead to ineffective team performances and even disastrous outcomes. A key component to ensure high-performing human-autonomy teams (HAT) is properly calibrated trust. Trust pertaining to many HAT tasks is dynamic, ever-changing in response to repeated human-autonomy interactions. Therefore, to ensure seamless HAT, there is an urgent need to account for this dynamic nature of trust and devise objective, unobtrusive means of inferring and predicting trust. Therefore, the main goal of this project is to develop a range of neurophysiological metrics and models capable of inferring and predicting single-trial trust dynamics in complex HAT settings and in real time. It seeks to breach key scientific and technological barriers that hinder machines from effectively and dynamically inferring and predicting their human partner's trust.

The postdoc will be supervised by Dr. Zhaodan Kong, an associate professor of Mechanical and Aerospace Engineering at UC Davis, and work closely with our collaborators, Drs. Allison Anderson and Torin Clark, at University of Colorado, Boulder. Additional information about Drs. Kong, Anderson, and Clark can be found at:
https://cphslab.engineering.ucdavis.edu
https://www.colorado.edu/faculty/anderson/
https://www.colorado.edu/faculty/clark-torin/

The successful candidate will be responsible for conducting high-quality research to advance theoretical, algorithmic, and/or experimental foundations for the development of metrics and models for real time inference and prediction of trust in human-autonomy teaming. The candidate is also expected to work with our collaborators at CU Boulder as well as AFRL to validate the developed metrics and models in simulated environments. The candidate will be involved in the presentation and publication of the results to our sponsors, the academic community, and the public. If the candidate is interested in translational research as well, there might be opportunities for the candidate to interact and collaborate with (or even co-mentored by) other faculty members at the UC Davis Center for Neuroengineering & Medicine.

Candidates must hold a Ph.D. in Aerospace Engineering, Biomedical Engineering, Computer Science, Neuroscience, Electrical Engineering, Mechanical Engineering, or a related discipline. Successful applicants must have extensive experience with collecting and analyzing EEG data. We are looking for applicants with demonstrably strong research skills, ideally, with multiple publications in top conferences and/or journals. Expertise with human-autonomy teaming, machine learning, network theory, and dynamical system theory would be huge pluses. Due to our project timeline, only those candidates who are currently in the U.S. will be considered.

Please send application with CV, including publication list and contact information of three references, to [email protected]. The position will be open until filled. Applicants should be available to start working on the project in winter/spring/summer of 2023.
The University of California is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age or protected veteran status. For the complete University of California nondiscrimination and affirmative action policy see: https://policy.ucop.edu/doc/4000376/NondiscrimAffirmAct

Under Federal law, the University of California may employ only individuals who are legally able to work in the United States.