Postdoctoral Research Associate- Decision Support Systems

6 months ago

Richmond, United States Commonwealth of Virginia Full time
The Department of Electrical and Computer Engineering in the College of Engineering at Virginia Commonwealth University, seek culturally and professionally diverse candidates to apply for the Postdoctoral Research Associate- Decision Support Systems position.

Since its inception in 1996, the Virginia Commonwealth University College of Engineering has brought innovative, real-world engineering education to Central Virginia. Comprised of five different departments plus the Dean’s office, the College of Engineering enrolls more than 1,700 undergraduate and 250 graduate students in several degree programs supported by approximately 600 full-time, part-time, and student employees. As part of a premier research university known for tenacity, love of the city of Richmond, and commitment to diversity and access, the College of Engineering values the significant and positive impact of our people and ideas in the promotion of regional and global prosperity involving research and life sciences.

Position Responsibilities:

The College of Engineering at Virginia Commonwealth University, Department of Electrical and Computer Engineering, has a postdoctoral position available. The successful candidate will have a unique opportunity to develop and expand upon a diversified technical skill set while making positive contributions to the design and development of decision support systems using Cyber Physical Systems (CPS) and Smart City projects. This specific postdoctoral position is expected to contribute to several funded projects.

Research projects for this position will involve developing and testing of decision support systems for smart cities using learning and model-based techniques. The ideal candidate will have a strong background in:

- System Optimization
- Learning-based System Design
- Large-scale and distributed control systems
- Cyber Physical systems

In this position, the successful candidate will have the opportunity to work and collaborate with a vast network of scientists and engineers.

Required Qualifications:

- Ph.D. in Electrical and Computer engineering or related fields
- Experience in optimization theory, decision support systems, and probability theory.
- Knowledge of machine learning technologies.
- Experience using edge computing for machine learning and deep learning frameworks.
- Developed high-quality software development, ideally as part of an open-source project, Python and Java preferred.
- Written publications in peer-reviewed journals and presentations at scientific conferences.
- Experience writing research proposals
- Ability to mentor junior team members and ensure the highest levels of laboratory safety.
- Excellent communication skills
- Demonstrated ability to work in multi-disciplinary teams.
- Ability to work under tight deadlines and short turnaround times
- The College of Engineering at VCU champions diversity, equity and inclusion in all that we do. Cultivating an ecosystem where differences are celebrated and our faculty, staff, and students have the opportunity to thrive is at the core of how we operate. The successful candidate will demonstrate experience that shows their commitment to fostering such an environment.

Preferred Qualifications:

Preferred qualifications include a record of superior academic or professional performance; the ability to be self-directed with broadly defined limits on assignments; excellent communication skills, both oral and written; and a demonstrated ability to interact effectively with diverse people in a highly multidisciplinary environment.

About the College of Engineering:
The College of Engineering’s mission is to create and grow a diverse community of exceptional students, faculty, staff, alumni, and industry partners that strive to create a common future for all where innovative, sustainable, and equitable solutions to global engineering challenges are realized for the benefit of this generation and future generations. Additional information about the department’s programs and faculty may be found at .

FLSA Status: Exempt
ORP Eligible: Yes

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