Education:
A bachelors degree from an accredited college or university with a major field of study in computer science information systems electrical engineering or a mathematicsintensive discipline which is closely related to the tasks to be performed
Technical:
Experience with fingerprint image analysis applications including Spectral Image Validation/Verification (SIVV) utility NIST Fingerprint Registration and Comparison Tool (NFRaCT) and NIST Fingerprint Image Quality (NFIQ).
Demonstrated ability to configure operating systems software and networking devices.
Demonstrated ability to develop software utilizing OpenCV and other opensource libraries.
Demonstrated ability to port image processing prototype code from MATLAB to C/C/C#
Demonstrated ability to manage and process collected data for statistical analysis.
Demonstrated ability to perform benchmarking optimization code profiling and performance testing.
Demonstrated ability to work with image compression algorithms applications and libraries
Demonstrated ability to work with programmatic control of scanners or digital cameras for image acquisition.
Experience:
Four years of demonstrated experience in:
Hardware customization configuration assembly and troubleshooting
Cross platform development and troubleshooting for multiple versions and variations of Windows and UNIX/LINUX operating systems in 32 and 64bit architectures.
Procedural objectoriented and scripted programming languages using C C C# VB.NET and Perl
Parallelization multithreading and hardwarebased optimizations for UNIX/Linux and Windows operating systems
Digital image processing and machine learning concepts and methods in software development including object detection perspective correction batch processing content extraction and analysis format conversion downandup sampling image segmentation and/or other filtering and transformation methods.
Resumes must demonstrate:
Expertise in biometric image analysis applications (e.g. NIST Fingerprint Image Quality NFIQ).
Proficiency in software development using C C C# OpenCV and other libraries.
Experience in crossplatform development for Windows and Linux.
Knowledge of hardware customization configuration and troubleshooting.
Background in statistical analysis and machine learning for biometric data processing.