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Postdoctoral Associate
Job no: 536195
Work type: Research Faculty
Senior management: Greater Washington, D.C Area
Department: Institute for Advanced Computing
Location: Alexandria, Virginia
Categories: Engineering, Research / Scientific
Job Description
Applications are invited for a full-time Postdoctoral Research Associate position within the Bradley Department of Electrical and Computer Engineering, Wireless@Virginia Tech, College of Engineering as well as the new Virginia Tech's Institute for Advanced Computing (IAC) located at the Washington DC metro.
The position involves conducting research in federated learning, and network optimization for 6G/FutureG wireless networks especially on the Internet of Intelligent Things under the supervision of Dr. Lingjia Liu (https://lingjialiu.ece.vt.edu). Successful candidates will have the chance to work with top-notched researchers from both academia and industry on future wireless systems spanning from novel physical layer waveforms designs (e.g., MIMO, OTFS) to online real-time neural receiver, from reflecting intelligent surfaces (RIS)/integrated sensing and communications (ISaC) to network design using O-RAN, from statistical learning theory to software defined radio (e.g., USRP) prototypes.
The Bradley Department of Electrical and Computer Engineering has both Electrical and Computer Engineering Ph.D. programs. Both programs continuously rank top in the U.S. The latest Global Universities ranking by U.S. News & World Report (USN&WR) places ECE Department at #2 nationally in the Electrical and Electronic Engineering category.
The position is based at the Virginia Tech Academic Building One in the greater Washington, D.C. area and offers opportunities to collaborate with industry partners and government research organizations. For more information, please visit: https://news.vt.edu/articles/2023/10/eng-futuregaward.html
Required Qualifications
• Ph.D. in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
• PhD must be awarded no more than four years prior to the effective date of appointment with a minimum of one year eligibility remaining.
• Demonstrated research expertise in federated learning, differential privacy, machine learning for internet of things, or related areas.
• Strong analytical, problem-solving, and programming skills.
• Written communication skills demonstrated through peer-reviewed publications, technical reports, or research manuscripts.
Preferred Qualifications
• Strong coding/programming skill (e.g., Python, C++, etc) is a plus.
• Experience with USRP prototypes is a plus.
• Experience with Nvidia computing platform is a plus.
• Experience collaborating in interdisciplinary research teams.
Overtime Status
Exempt: Not eligible for overtime
Appointment Type
Restricted
Salary Information
70,000
Hours per week
40
Review Date
5/4/2026
Additional Information
The successful candidate will be required to have a criminal conviction check.
About Virginia Tech
Dedicated to its motto, Ut Prosim (That I May Serve), Virginia Tech pushes the boundaries of knowledge by taking a hands-on, transdisciplinary approach to preparing scholars to be leaders and problem-solvers. A comprehensive land-grant institution that enhances the quality of life in Virginia and throughout the world, Virginia Tech is an inclusive community dedicated to knowledge, discovery, and creativity. The university offers more than 280 majors to a diverse enrollment of more than 36,000 undergraduate, graduate, and professional students in eight undergraduate colleges, a school of medicine, a veterinary medicine college, Graduate School, and Honors College. The university has a significant presence across Virginia, including Blacksburg, the greater Washington, D.C. area, the Health Sciences and Technology Campus in Roanoke, sites in Newport News and Richmond, and numerous Extension offices and research institutes. A leading global research institution, Virginia Tech conducts more than $650 million in research annually.
Virginia Tech endorses and encourages participation in professional development opportunities and university shared governance. These valuable contributions to university shared governance provide important representation and perspective, along with opportunities for unique and impactful professional development.
Virginia Tech does not discriminate against employees, students, or applicants on the basis of age, color, disability, sex (including pregnancy), gender, gender identity, gender expression, genetic information, ethnicity or national origin, political affiliation, race, religion, sexual orientation, or military status, or otherwise discriminate against employees or applicants who inquire about, discuss, or disclose their compensation or the compensation of other employees or applicants, or on any other basis protected by law.
If you are an individual with a disability and desire an accommodation, please contact Stuart Cline at stuart90@vt.edu during regular business hours at least 10 business days prior to the event.
Advertised: April 20, 2026
Applications close:
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