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ITL MSE Grant Application Process

NOTICE:  Measurement Science and Engineering (MSE) Notice of Funding Opportunity (NOFO)

To find instructions and submit an application go to

Questions concerning the ITL program may be directed to:
Alex Folk
Information Technology Laboratory
100 Bureau Drive, Stop 8900
Gaithersburg, MD 20899-8420
(301) 975-8089

Federal Agency Name: National Institute of Standards and Technology (NIST)
Funding Opportunity Title: Measurement Science and Engineering (MSE) Research Grant Programs
Funding Opportunity Number: 2021-NIST-MSE-01 (NEW)
Anticipated Funding Amount: $10,000 - $500,000 per year range and with project performance periods of up to five years, consistent with multi-year funding policy. 
Funding Instrument: Grant or Cooperative Agreement

Evaluation Criteria

The evaluation criteria that will be used in evaluating applications considered by the ITL Grant Program and assigned weights are as follows, for a total maximum of 30 points:

  1. Technical Quality and Intellectual Merit. The extent to which the proposed activities are innovative, original, or potentially transformative; whether the research plan is well-reasoned, well-organized and based on a sound rationale; and whether the plan incorporates a reasonable mechanism to assess success. (0-10 points)
  2. Potential Impact of the Results. The probability of achieving technical application of the results and the likelihood for the project to exert a sustained, powerful influence on the research field(s) involved. The extent to which the applicants approach aligns with ITL's programs and mission (See Section I.6. of this NOFO). (0-10 points)
  3. Capability to Perform the Work. The extent to which the applicant organization, any proposed partner organizations, and key personnel, have the qualifications (e.g., training, experience, accomplishments) and resources (e.g., facilities, equipment) needed to support the proposed project and successfully achieve the stated objectives. (0-5 points)
  4. Match of Budget to Proposed Work. Assessment of the budget compared to the proposed work to ascertain the reasonableness of the request. (0-5 points)

Program Description 

Program Description: The mission of the Information Technology Laboratory (ITL) is to cultivate trust in information technology (IT) and metrology and is accomplished using its world-class measurement and testing facilities and encompassing a wide range of areas of computer science, mathematics, statistics, and systems engineering.

The ITL Grant Program provides financial assistance to support the conduct of research or a recipient’s portion of collaborative research consistent with the ITL’s missions to support research in the following fields: Advanced Network Technologies, Applied and Computational Mathematics, Artificial Intelligence, Big Data, Biometrics, Cloud Computing, Cyber-Physical Systems, Cybersecurity, Forensic Science, Health Information Technology, Human Factors and Usability, Information Access, Information Processing and Understanding, Internet of Things (IoT), Metrology Infrastructure for Modeling and Simulation, Privacy Engineering, and Statistics for Metrology.

Additional information about the ITL and ITL Programs may be obtained at

Financial support may be provided to attend education and outreach programs, conferences, workshops, or other technical research meetings that are relevant to the mission of the ITL. Financial support may also be provided to organizations sponsoring conferences, workshops, or other technical events that are relevant to the mission of the ITL. However, NIST cannot be an official sponsor or cosponsor for any event funded through this program.

All applications submitted to the ITL Grant Program must be in accordance with the program objectives listed below. The contact person for the ITL Grant Program, who may be contacted for clarification of program objectives, is Melissa Banner and she may be reached at (301) 975-5245 or by e-mail at

Artificial Intelligence Program: NIST contributes to the research, standards, and data required to realize the promise of AI as an enabler of American innovation across private and public sectors. To achieve trustworthy AI systems, stakeholders need to develop (and subsequently ensure understanding and use of) the building blocks for trustworthy AI systems and the associated measurement, standards, and tools to implement those building blocks when developing, using, and testing AI systems. NIST develops vocabulary and measurements needed for technical requirements of trustworthy AI. NIST plans and carries out its AI work in close collaboration with the private and public sectors, often serving as a convener. Specific topics of interest include foundational research on examining and measuring various aspects and technical requirements of AI trustworthiness, including the accuracy, reliability, security, safety, privacy, bias, and explainability of AI systems.

Advanced Network Technologies Division (ANTD) provides expertise in Network Science and Engineering. ANTD develops knowledge about networks to understand their complexity and inform their future design. It seeks to discover and understand common principles and fundamental structures underlying networks and their behaviors. ANTD studies the processes underlying networks evolution and the paradigms for network engineering to enhance their trustworthiness, reliability, security, and robustness. ANTD responds to national priorities with programs in Internet Infrastructure Protection, Cloud Computing, 5G/6G Mobile Networks, Next Generation Internet (NGI), Internet of Things, Quantum Networking, Smart Grid, Smart Manufacturing, and Localization. Specific objectives of interest in these areas of research include: Advanced Distributed Denial of Service Detection and Mitigation Techniques; Graph Theory and Network Science; Information Centric Networking; Internet Inter-Domain Routing Robustness; Measurement Science for Complex Networked Information Systems; Network Anomaly Detection/Evaluation; Network Function Virtualization/Software Defined Networking; Network Programming; Next Generation Internet Architectures; Secure Communications for Cloud; Secure Distributed Computation; Secure Domain Name System Technologies; and Trusted Ad Hoc Networks.

Applied and Computational Mathematics Division (ACMD) nurtures trust in metrology and scientific computing through the development and application of advanced mathematical and computational techniques and tools. Current topics of interest include: the Mathematics of Special Functions; Neuromorphic Computing; Quantum Information Science; Mathematical Modeling in Biotechnology; and Scientific Visualization.

Applied Cybersecurity Division (ACD) implements practical cybersecurity and privacy through outreach and effective application of standards and best practices necessary for the U.S. to adopt cybersecurity capabilities. ACD establishes cybersecurity standards and guidelines in an open, transparent, and collaborative way; provides cybersecurity testing and measurement (from developing test suits and methods to validating cryptographic modules); and conducts research in applied cybersecurity. Specific objectives of interest in these areas of research include: Cybersecurity Awareness, Training, Education, and Workforce Development; Cybersecurity Risk Management and Measurement Techniques; Identity and Access Management; Internet of Things Cybersecurity, and Privacy Engineering.

Computer Security Division (CSD) develops cybersecurity standards, guidelines, tests, and metrics to protect federal information systems. CSD helps to develop innovative security technologies that enhance the nation’s ability to address current and future computer and information security challenges. CSD’s research focuses on cryptography, automation, identity and access management, the Internet of Things, and public safety networks. The Division maintains a Computer Security Resource Center (CSRC), which provides access to NIST's cybersecurity-and information security-related projects, publications, news, and events. Specific objectives of interest in these areas of research include: Cryptography and Cryptographic Test Methods; Light Weight Cryptography; Post Quantum Cryptography; Security Testing Tools and Metrics; Semantics; Service Oriented Architecture; Privacy Enhancing Cryptography, Entropy Assessment; Cybersecurity Conformance Testing; Security Automation; and Security Engineering.

Information Access Division (IAD) supports technologies used to access complex information relating to human action, behavior or characteristics. Through collaborations with industry, academia, and the federal government, IAD enables the advancement of these technologies for commercial usage. IAD provides standards and measurements to accelerate this evolution. Specific objectives of interest in these areas of research include: Active Evaluations; Biometrics for Search; Verification and Clustering of Identity, Computer Vision/Video Analytics, Data Quality for Analytics and Machine Learning; Query, Indexing, and Access Technology; Usable (human factors) Security; Human Language Technology; Image/Media Analysis; and Search and Retrieval Algorithms.

Software and Systems Division (SSD) works with industry, academia and other government agencies to accelerate the development and adoption of correct, reliable and testable software. This collaborative effort leads to increased trust and confidence in deployed software and methods to develop better standards and testing tools. SSD focuses on advances in state-of-the-art software testing and facilitates the transfer of applications and technologies into national infrastructures and commercial sectors. Specific objectives of interest in these areas of research include: Artificial Intelligence, Digital Forensics; Data Analytics; Data Storage; Cloud Computing; Health IT; High Performance Computing; Image Analytics; IoT for Health Applications; Material Genome Initiative; Medical Device Interoperability; Software Assurance; Systems Biology; Systems Interoperability.

Statistical Engineering Division (SED) conducts fundamental and applied statistical research on problems in metrology; develops and applies best practices for the characterization of measurement uncertainty, in particular to enable the intercomparison of measurements in the context of interlaboratory studies and calibrations; and implements methods and techniques for experimental design, data analysis, statistical modeling and probabilistic inference in computer software. Specific objectives of interest in these areas of research include: Statistical Methods in Forensic Science; and Statistics for Metrology.


Created April 26, 2016, Updated February 2, 2021