Associate Research Scientist (PREP0004940

Johns Hopkins, founded in 1876, is America''s first research university and home to nine world-class academic divisions working together as one university.

Salary : $ a year

Johns Hopkins University:
Whiting School of Engineering:
Office of Research and Translation

PREP Research Associate

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields.

Individuals in this position will perform technical work supporting the collaboration''s scientific research.

Research

Title:

Data Scientist / Computer Scientist – Standardized AI-Ready Dataset Frameworks for AI-Based Radio Access Networks (AI-RAN)

The work will entail:

NIST seeks an experienced researcher to support the development of standardized frameworks for "AI-ready" datasets in the Radio Access Network (RAN), in support of U.S. leadership in 6G standardization. The successful candidate will survey existing wireless data repositories and relevant standards activities, participate in multi-modal measurement campaigns, and develop technical guidelines for AI-ready RAN dataset creation. The candidate is expected to convey the results of their work through a NIST Technical Note and contribute to standards bodies such as the AI-RAN Alliance, O-RAN Alliance, and 3

GPP.

U.S. Citizen Preferred

Key responsibilities will include but are not limited to:

• Survey existing multi-modal wireless data repositories and standards activities to assess AI-readiness and identify gaps, limitations, and potential enhancements.
• Support Integrated Sensing and Communication (ISAC) measurement campaigns to capture, synchronize, and label RF, LiDAR, and camera data.
• Develop data processing pipelines to evaluate and compare dataset formats for AI/ML applications.
• Co-author a NIST Technical Note on guidelines for creating standardized AI-ready RAN datasets.
• Develop contributions to standards bodies and industry consortia, and ensure outputs are publicly disseminated through proper NIST processes.

Qualifications

• Master’s or Ph.D. degree in data science, computer science, computer engineering, electrical engineering, or a closely related field.
• 1+ years of relevant experience in the design, collection, and processing of large-scale multi-modal datasets, preferably in wireless communications or AI/ML applications.
• 1+ years of relevant experience with modern data engineering tools and frameworks (e.g., Python, PyTorch/Tensor Flow, MATLAB, or similar) to enable data acquisition, storage, labeling, and analysis.
• Familiarity with wireless communications systems, including RF signal processing concepts such as I/Q samples, channel state information (CSI), and power delay profiles.
• Strong oral and written communication skills, with the ability to contribute to technical reports and standards documents.

Additional Desirable Skills, Expertise and

Qualifications:

• Experience with multi-modal sensing systems, including LiDAR, camera, and radar data collection and synchronization.
• Familiarity with the Findable Accessible Interoperable and Reusable (FAIR) data principles, public data repositories, data schemas, versioning, and open dataset documentation practices.
• Experience with GPU-accelerated hardware platforms and software engineering including NVIDIA GPUs and CuPy/CUDA/C++ programming.
• Familiarity with 5G/6G wireless standards and AI/ML integration frameworks being developed by 3
  
  GPP, O-RAN Alliance, or the AI-RAN Alliance.
• Experience with Integrated Sensing and Communication (ISAC) use cases such as object detection, human detection, or drone tracking. Experience in authoring research publications and presentations documenting results of experiments, modeling, and analysis research.

Equal Employment Opportunity Statement

Salary Range

The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University''s good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate''s geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.

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Equal Opportunity Employer

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