CTL 2026 SURF Program

Internships with the Communications Technology Laboratory

The 2026 SURF program is designed to provide a paid 11-week hands-on research experience in communications technology. CTL's SURF projects offer virtual and in-person opportunities in Boulder, Colorado, and Gaithersburg, Maryland.  Interns are awarded up to a $7,810 stipend, with travel and housing allowances available for those who live outside of the NIST immediate area. Applications are due January 26, 2026. 

With expertise honed over decades of research in antennas and wireless propagation, materials science and electronics testing, as well as communications network protocols and standards, CTL serves as an independent, unbiased arbiter of trusted measurements and standards to government and industry. We focus on developing precision instrumentation and creating test protocols, models, and simulation tools to enable a range of emerging wireless technologies. Click here for additional information on CTL.  

Opportunities located in Boulder:  CLICK HERE TO APPLY 

RF Technology Division (Read More)

Opportunities in Gaithersburg  CLICK HERE TO APPLY 

Wireless Networks Division (Read More)

673-1 Simulation and Modeling of Resilient Mobile Networks

Wesley Garey, 301-975-5190, wesley.garey [at] nist.gov (wesley[dot]garey[at]nist[dot]gov)

Wireless mobile networks have become an integral part of everyday life as cellphones have become ubiquitous in today’s world. These gains have taken place over several decades with advent of 3G which enabled data communication, 4G that enabled broadband connectivity, and 5G that is now capable of providing ultra-fast speeds and ultra-low latency. The latest enhancements to 5G and moving forward with 6G will provide several features with the intended purpose of extending network coverage and maintaining user connectivity. This includes the use of Non-Terrestrial Networks (NTN), i.e., satellites, and direct device-to-device (D2D) communication. The NIST Wireless Networks Division (WND) is actively developing next-generation cellular communications standards and performing research studies around network resiliency and ubiquitous connectivity via the use of NTN and D2D communication.

The student selected for this project will have the opportunity to work alongside members of WND to create and enhance software tools used to evaluate wireless communication technologies. This includes developing visualization tools to demonstrate simulation events, utilities to facilitate Continuous Integration and Deployment (CI/CD) of the developed tools, and simulation models in ns-3 and other platforms to simulate emerging wireless technologies. The student selected for this project will code using a variety of programming languages, regularly use the Linux command line, and manage code using a version control system such as Git.

Desired Skills/Experience

Major in Electrical Engineering, Computer Science, or a related field with some programming experience. Knowledge of C++, Python, and/or Bash is strongly recommended.  Background in wireless networking (principles of the Internet and cellular communications).  Experience using Git.  Interests in computer models and simulations of future networks.  Ability to collaborate with a team and good communication skills.

673-2 Prototype and Evaluation of Security Protocols for 5G/6G Mobile Networks

Scott Rose and Oliver Borchert, 301-975-8439, scott.rose [at] nist.gov (scott[dot]rose[at]nist[dot]gov)

5G/6G Open-Radio Access Networks (O-RAN) technologies aim to transform radio access networks from single-vendor solutions based on proprietary appliances to a disaggregated network architecture of components and functions, featuring standardized open interfaces designed for deployment in virtualized and cloud-native environments. NIST is actively engaged in O-RAN Alliance standards development, focusing on enhancing the security of virtualized, cloud-native O-RAN functions. We see this area as having both the most significant potential to increase overall network security and the most significant potential risk to the eventual commercial viability of O-RAN technologies. Some of these new technologies have not been designed with mobile networks in mind, but may help secure next-generation telco networks. This project will involve prototyping new protocols and methods of providing secure communication between virtualized workloads. This involves working on the overall design, development, deployment, and testing in a cloud-native environment. Knowledge of virtualization platforms, such as Kubernetes, is helpful but not necessary.

Desired skills/experience

Linux, Kubernetes / Docker, service-based architectures, some programming (Python, Golang, NodeJS, or similar), dev-ops / network programming, network protocols/tools/technologies (HTTP, TLS, PKI, OAUTH, Wireshark), security scanning tools.

673-3 ML Sensing Abstraction for  ISAC System Level Simulation

Anirudha Sahoo, 301-975-4439, anirudha.sahoo [at] nist.gov (anirudha[dot]sahoo[at]nist[dot]gov)

Future wireless networks won't just transmit data; they will use radio waves to sense the physical world, acting like a radar to detect objects and their locations. This is known as Integrated Sensing and Communications (ISAC).

To design these systems, researchers run complex simulations that model exactly how radio waves bounce off objects. These simulations are extremely accurate, but they are also incredibly slow and computationally heavy. It is currently impractical to run these simulations at a large scale to test entire networks.

Instead of calculating the physics of every radio wave, we want to build a Machine Learning model that can "predict" the outcome instantly. In this project, the student will build a fast "surrogate model" (an AI substitute). The student will train this model to look at the geometry of a scene, e.g., where the base station is, where the target is, and how many antennas are used, and accurately predict how well the sensing will work. The objective is to teach an AI to replicate the results of a complex physics engine, but in a fraction of the time.

Desired skills/experience

Essential skills include a solid understanding of Machine Learning (ML) concepts and model training, proficiency in Python or MATLAB, and a good understanding of Linear Algebra. Preferred skills include understanding the basics of signal processing concepts and familiarity with wireless / Radio Frequency (RF) concepts such as, Signal-to-Noise Ratio (SNR), Orthogonal Frequency-Division Multiplexing (OFDM), and antenna arrays.

Smart Connected Systems Division (Div. 674) (Read More)

674-1 Testable Cyberphysical System Specifications

Charles Manion, 301-975-4251, charles.manion [at] nist.gov (charles[dot]manion[at]nist[dot]gov)

This project provides an opportunity for a student to learn systems modelling in the new Systems Modeling Language v2 (SysML2) standard by developing modelling methods to describe and test spatiotemporal behavior. SysML is a widely-used standard for describing complex systems, such as telecommunication networks, spacecraft, naval vessels, and manufacturing systems, enabling large engineering teams and AI to collaborate in designing and analyzing them. SysML v2 adds new spatiotemporal modeling capabilities that enables intended behavior to be described in a much more detailed and testable manner.

SysPhS adds 1D modeling to SysML and defines translation to 1D simulation tools, such as OpenModelica and Mathworks Simulink/Simscape.  This kind of modeling assembles physical and signal components that include ordinary differential and differential algebraic equations forming a system of equations solved by time-stepped simulators.  It is applicable to a wide variety of cyberphysical systems, including signal processors, electrical, mechanical, hydraulic, and thermal. This project will focus on investigating how to specify intended behavior in SysML2 and test that systems simulations have said intended behavior.

The student will (A) Learn how to model in SysML 2. (B) Model a system in SysML2 and investigate techniques to test its behavior (C) Develop new physical/signal component libraries for SysPhS in SysML 2.

Desired skills/experience

Preferred major: Mechanical, Aerospace, or Electrical Engineering. Required: Calculus based physics or dynamics or circuit theory. Basic programming experience such as with Python or MATLAB. Recommended: Experience with 1D modeling and simulation such as Modelica or Simulink. Has taken Numerical methods, linear systems and signals, or controls. Some familiarity with object-oriented programming.