Postdoctoral Research Associate – Link Lab at University of Virginia

The Departments of Electrical and Computer Engineering and Computer Science in the School of Engineering and Applied Science at the University of Virginia seek to hire a postdoctoral research associate in the Link Lab ( https://engineering.virginia.edu/link-lab ) in the area of Learning Enabled Cyber-Physical Systems (CPS) for Smart Health .

This position will support research projects on design and validation of Context-Aware Cognitive Assistant Systems that combine wearable sensing, embedded computing, and artificial intelligence capabilities (such as speech processing, computer vision, natural language processing, and explainable machine learning) to provide situational awareness and safety assurance in the human-in-the-loop CPS , with applications to emergency response ( https://www.nist.gov/ctl/pscr/funding-opportunities/past-funding-opportunities/psiap-augmented-reality/context-aware ).

The candidate is expected to produce high quality and novel research ideas for publications in top-tier conferences and journals, contribute to writing research grant proposals, present research findings at international conferences and PI meetings, and build and maintain CPS testbeds in collaboration with a multi-disciplinary team of faculty, graduate students, and undergraduate researchers. They will also be expected to take a leadership role within the lab, which involves assisting in the training of graduate and undergraduate students.

QUALIFCATIONS: Candidates must have a Ph.D. in Computer Science, Electrical and/or Computer engineering by the start date.

o Research experience and significant implementation experience in Machine Learning, Artificial Intelligence, and Cyber-Physical Systems, is strongly preferred.

o Proficiency with development, implementation, and evaluation of advanced data analytics and machine learning algorithms in common programming languages (e.g., C/C++ and Python).

o Demonstrated ability to be self-motivated, willing to take the lead and work independently and as a team member.

o Demonstrated proficiency in high-quality technical writing and clear communication in English.

o Demonstrated experience in working with a diverse group of researchers and sponsors or varying technical expertise.

APPLICATION PROCEDURE: Apply online at https://uva.wd1.myworkdayjobs.com/UVAJobs and attach a cover letter, curriculum vitae, and the contact information for three individuals who can provide professional reference letters (name, email address, telephone number, and address).

Please note that multiple documents can be uploaded in the box .

APPLICATION DEADLINE: Review of applications will begin on May 21, 2023, but the position will remain open until filled. The University will perform background checks on all new hires prior to employment.

This is a one-year appointment; however, the appointment may be renewed for an additional two, one-year increments, contingent upon available funding and satisfactory performance.

For additional information about the position, please contact Dr. Homa Alemzadeh ( alemzadeh@virginia.edu ) and Dr. Jack Stankovic ( stankovic@virginia.edu ).

For information about the Link Lab go to https://engineering.virginia.edu/link-lab/

For questions about the application process, please contact Rich Haverstrom, Faculty Search Advisor, at rkh6j@virginia.edu .

For more information on the benefits available to postdoctoral associates at UVA, visit postdoc.virginia.edu and hr.virginia.edu/benefits .

COVID Vaccination Requirement and Guidelines

Please visit the UVA COVID-19 Job Requirements and Guidelines webpage prior to applying for current information regarding vaccination requirements and guidelines for employment at UVA.

The University of Virginia, i ncluding the UVA Health System which represents the UVA Medical Center, Schools of Medicine and Nursing, UVA Physician’s Group and the Claude Moore Health Sciences Library, are fundamentally committed to the diversity of our faculty and staff. We believe diversity is excellence expressing itself through every person's perspectives and lived experiences. We are equal opportunity and affirmative action employers. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender identity or expression, marital status, national or ethnic origin, political affiliation, race, religion, sex (including pregnancy), sexual orientation, veteran status, and family medical or genetic information.