This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title:
Modeling aggregate radio frequency emissions from outdoor 4G and 5G cellular deployments
The work will entail:
Conduct research comparing models of received aggregate radio frequency (RF) emissions from 4G and 5G cellular deployments. Examine the effects of different path loss and clutter models on individual emitter contributions and aggregate emission calculations. Compare model predictions to field measurements from ongoing NIST projects.
Key responsibilities will include but are not limited to:
- Develop and implement algorithms and models for aggregate RF emissions using Python and/or MATLAB.
- Process field measurements and compare with modeled results using various simulation tools.
- Collaborate with other researchers and engineers to advance the state-of-the-art in aggregate emissions modelling and analysis.
- Present research findings in peer-reviewed publications and presentations.
Qualifications
- U.S. Citizenship
- Ph.D. in Electrical Engineering, Computer Science, or a related field received within the last 5 years.
- Strong background in electromagnetic propagation.
- Strong background in wireless communication systems and technologies.
- Proficiency in programming languages such as Python and MATLAB.
- Ability to collaborate effectively with research professionals and work independently.
- Excellent analytical and problem-solving skills.
- Strong oral and written communication skills.
- Preferred: Strong background in signal processing and statistics.
- Preferred: Track record of peer-reviewed publications.
The university is an Equal Employment Opportunity/Affirmative Action employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.