RF Engineering Scientist R25615
Please Note: In order to be considered for this position, you MUST be a US Citizen and apply through the ARL Workday website.
The Signal and Information Sciences Lab (SISL) delivers capabilities to government customers for diverse applications, such as information and network science, cybersecurity, natural language processing, geospatial remote sensing, and modeling and simulation.
SISL is seeking a motivated individual to support research and development tasks relating to algorithm development and data analytics for RF networks. This includes tasks such as predicting propagation loss, testing new algorithms for link prediction, and running network simulators. The ideal candidate will have experience with both RF networks and data science.
- Developing, training, testing, and deploying solutions to support requirements for RF network projects.
- Writing flexible and maintainable software code according to software best practices.
- Reviewing peer-developed software to improve team designs and implementations.
- Deploying and supporting software delivered outside of ARL:UT.
- Documenting new and legacy software code for internal review and external deliveries.
- Other related functions as assigned.
- Bachelor’s degree in Engineering, Computer Science, or other related discipline.
- Three years of related experience.
- Experience in at least one of the following: RF networks, RF network data, network simulators, wireless networks
- Proficiency using Python for algorithm development, testing, and implementation.
- Experience using common data science tools and techniques for data analysis.
- Demonstrated ability to work with subject matter experts when developing analytics.
- Experience working on Linux and Windows operating systems.
- Demonstrated ability to work effectively, both independently and collaboratively, with a strong commitment to contribution and enabling the entire team.
Applicant must have a dynamic skill set, willing to work with new technologies, be highly organized and capable of planning and coordinating multiple tasks and managing their time. The position will require attention to detail, effective problem solving skills and excellent judgment. Ability to work independently with sensitive and confidential information, maintain a professional demeanor, work as a team member without daily supervision and effectively communicate with diverse groups of clients. Able to work under pressure and accept supervision. Regular and punctual attendance.
US Citizen. Applicant selected will be subject to a government security investigation and must meet eligibility requirements for access to classified information at the level appropriate to the project requirements of the position.
- Master’s degree in Engineering, Computer Science, or other related discipline.
- Experience in multiple of the following: RF networks, RF network data, network simulators, wireless networks
- Experience with either NS-3 or EMANE network simulators
- Demonstrated ability to implement and test machine learning based techniques in relevant or related problem domains.
- Ability to implement and test algorithms in a research environment.
- Cumulative GPA of 3.0.
An agency designated by the federal government handles the investigation as to the requirement for eligibility for access to classified information. Factors considered during this investigation include but are not limited to allegiance to the United States, foreign influence, foreign preference, criminal conduct, security violations, drug involvement, the likelihood of continuation of such conduct, etc.
Please mark "yes" on the application question that asks if additional materials are required. Failure to attach all additional materials listed below may result in a delay in application processing.
Visit our website (www.arlut.utexas.edu) for additional information about Applied Research Laboratories.
UT Austin offers a competitive benefits package that includes:
· 100% employer-paid basic medical coverage
· Retirement contributions
· Paid vacation and sick time
· Paid holidays
Please visit our Human Resources (HR) website to learn more about the total benefits offered.
- Standard office conditions
- Repetitive use of a keyboard at a workstation
- Use of manual dexterity
- Possible weekend, evening and holiday work
- Possible interstate/intrastate travel
- 3 work references with their contact information; at least one reference should be from a supervisor
- Letter of interest
- Unofficial college transcript