Lead Image Scientist
Freedom Technology Solutions Group is seeking a Lead Image Scientist. The Lead Image Scientist (IS) will serve as a technical specialist for research, evaluation and verification of highly complex image and video processing systems for geospatial intelligence sensors, systems, and applications. The Lead IS will provide expert-level consultation, problem solving, and verification for all GEOINT quality assessments, studies, and standards. The Lead IS will provide detailed recommendations and risk assessments to Government and technical leadership. The Lead IS will design, develop, evaluate, and verify the implementation of complex image processing software products, algorithms, and workflows. The Lead IS will mentor and guide junior image scientists in the development of criteria for testing algorithm and system’s cognitive performance objectively from an end-user perspective, as well as perform evaluation and testing on simulated and operational data.
Required Qualifications:
- Active TS/SCI with the ability to obtain a Poly
- Master's degree/PhD in Imaging Science, Physics, Engineering, Mathematics or quantitative science field and 10 years of experience as a Image Scientist
- Demonstrated knowledge of digital imaging systems principles and practices
- Experience supporting the development, testing, and analysis of image collection systems
- Experience applying engineering standards, principles, theories, concepts and techniques to solve complex problems associated with image product formation from raw sensor and associated metadata
- Experience or working knowledge with advanced photogrammetric techniques and principles
- Experience performing image system simulations to produce realistic test data to support system validation and testing
- Experience or demonstrated ability to develop, assess, and implement Image Quality Equations
- Experience building image processing algorithms
- Experience programming in Matlab and/or Python, C++, or other equivalent programming languages
- Experience analyzing and assessing quality of image data across the full-range of sensor types, sources, and phenomenology’s
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