NIST PREP Student Software Engineer
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Summary
A student software engineer role supporting NIST research: build deepfake-generation, benchmarking, and detection pipelines in Python on Linux/GPU systems, plus a secure web evaluation platform with authentication and controlled dataset access. Day to day is research software development, reproducible evaluation infrastructure, and quantitative performance analysis.
You will develop deepfake-generation and benchmarking pipelines, metadata and dataset-validation tools, and baseline detection algorithms. You will build reproducible evaluation infrastructure, deploy tools on Linux and GPU systems, and create a secure web platform with authentication, controlled dataset access, and administrative capabilities.
Responsibilities
- Develop deepfake and synthetic-data generation pipelines
- Implement metadata handling and dataset-validation tools
- Build deepfake media benchmarking infrastructure
- Implement baseline deepfake detection algorithms
- Deploy detection tools on Linux servers and GPU clusters
- Implement evaluation metrics and reproducible evaluation pipelines
- Conduct quantitative performance analysis
- Design, implement, and maintain a secure evaluation web platform
- Build authentication, controlled dataset access, and administrative functionality
Requirements
- Senior undergraduate or graduate student in Computer Science, Software Engineering, or a related field
- Strong Python proficiency
- Linux and Bash scripting experience
- Background in audio, image, or video processing and analysis
- Ability to work independently and in collaborative research environments