This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
Research Title:
Computer Vision AI models for Additive Manufacturing image processing
The work will entail:
The NIST Information Technology Lab (ITL) and Engineering Lab (EL) are collaborating on a project for real-time image processing for Additive Manufacturing. To handle real-time constraints, computations on Field Programmable Gate Array (FPGA) devices will need to be enabled, likely involving both traditional Computer Vision algorithms and Deep Learning models.
We plan on instrumenting a hard real-time system that can meet the time sensitive deadlines for detecting sparks from a high-speed camera that is monitoring the interaction between the melt pool and laser. There are three methodologies to consider.
1. The camera contains a built-in FPGA that can process images as they are captured.
2. The capture card has a slightly higher-end FPGA.
3. The capture card can transfer image data into system memory, allowing the host system to process images using either the CPU, GPU, or a combination of both.
To this end, we are seeking a Computer Scientist who will focus on developing algorithms to process frames in real-time from a high frame rate camera. The processing algorithms may utilize the camera’s built-in Field Programmable Gate Arrays (FPGA), the capture card’s built-in FPGA, or traditional computer CPUs and GPUs.
Key responsibilities will include but are not limited to:
- Develop image analysis algorithms that target the highspeed camera’s FPGA.
- Develop image analysis algorithms that target the capture card’s FPGA.
- Develop image analysis algorithms that target the traditional computer’s CPU(s) and GPU(s).
- Measure real-time throughput for developed image analysis workflows.
- Create AI/Deep learning workflows for training AI models for analyzing images in a series.
Qualifications
- A completed or in-process graduate degree in Computer Science, Engineering, Manufacturing, or a related field.
- 1—2 years of relevant experience.
- Familiarity with image analysis algorithms.
- Familiarity with FPGA programming.
- Familiarity with CPU and/or GPU image analysis.
- Experience with AI/Deep learning workflows, such as LSTMs.
- Ability to develop prototypes of tools needed to analyze data.
- Strong oral and written communication skills.
- Candidates must be eligible to obtain a Department of Commerce background check for facility access.
The university is an Equal Employment Opportunity employer that does not unlawfully discriminate in any of its programs or activities on the basis of race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or expression, or on any other basis prohibited by applicable law.