Assistant Research Scientist (PREP0004317)
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
- Deepfake and Synthetic Data Generation and Automated Benchmarking Dataset Pipeline Development, including but not limited to: developing automated or semi-automated state-of-the-art deepfake image/audio generation pipelines; implementing metadata handling and dataset validation tools; building infrastructure for deepfake media benchmarking; etc.
- Deepfake Analytic AI System Implementation: Implement baseline deepfake detection algorithms; design modular, well-documented, and maintainable codebases; deploy deepfake detection tools on Linux servers and GPU clusters; ensure reproducibility and performance optimization; maintain cross-platform compatibility (Linux, macOS, Windows); implement containerized solutions (Docker-based workflows) as needed.
- Scoring Package & Evaluation Infrastructure: Implement evaluation metrics (ROC curves, AUC, confusion matrices, robustness analysis); develop reproducible evaluation pipelines; conduct quantitative performance analysis across different data subsets.
- Web Platform Development: Design, implement, and maintain a secure, scalable evaluation web platform that includes a user authentication system (login, registration, role-based access control), a dataset release portal with controlled access, and an admin dashboard for dataset and user management. The technology stack may include (but is not limited to) Python, React or modern JavaScript frameworks, PostgreSQL, Docker, and Linux-based deployment environments.
Qualifications
This individual must have the following minimum knowledge, skills, and abilities:
- Senior undergraduate or graduate student in Computer Science, Software Engineering, or a related field
- Strong proficiency in Python to support timely project delivery
- Experience working in a Linux environment and with shell scripting (Bash) is required
- Background in media (audio, image, or video) processing and analysis
- Ability to work independently as well as in collaborative research environments
Furthermore, the following knowledge skills, and abilities are preferred:
- GPU programming or AI model development experience
- Experience with web development (HTML, CSS, JavaScript)
- Experience developing backend services (Flask, Django, FastAPI, Node.js, etc.)
- Previous experience with generative AI tools, including deepfake technologies and large language models
- Experience in cross-platform software development (Linux, macOS, Windows)
- Experience or interest in machine learning and AI system testing and evaluation
- Experience with database management (e.g., PostgreSQL)
- Experience with Jupyter Notebooks, R, Shiny, and interactive data visualization
Key responsibilities will include but are not limited to:
Qualifications:
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Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor’s degree holders, graduate students, master’s degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
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