Assistant Research Scientist (PREP0003758)

Johns Hopkins University; Baltimore (MD); On-site; USD 60,000 - 80,000; Full time

Job summary

Johns Hopkins University is seeking a PREP Research Associate to work with the National Institute of Standards and Technology (NIST) on innovative image processing for additive manufacturing. This role requires the development of algorithms for real-time data processing using FPGAs and AI techniques.

The ideal candidate will have a graduate degree in Computer Science or Engineering and experience in image analysis and deep learning. Join us in pushing the boundaries of manufacturing technology!

Qualifications

• Completed or in‑process graduate degree in Computer Science, Engineering, Manufacturing, or a related field.
• 1–2 years of relevant experience.
• Strong oral and written communication skills.

Responsibilities

• Develop image‑analysis algorithms targeting FPGA.
• Develop image‑analysis algorithms for CPUs and GPUs.
• Create AI/Deep‑learning workflows for training models.

Skills

Image‑analysis algorithms

FPGA programming

AI/Deep‑learning workflows

CPU/GPU image analysis

Education

Graduate degree in Computer Science, Engineering, Manufacturing, or related field

Job description

PREP Research Associate

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST supports collaborative research between its staff and academic institutions and requires that the receiving institution have a PREP award. Employees in this role will perform technical work that underpins the scientific research of the collaboration.

Research Title

Computer Vision AI models for Additive Manufacturing image processing

Project Overview

The NIST Information Technology Lab (ITL) and Engineering Lab (EL) are collaborating on real‑time image processing for additive manufacturing. Real‑time constraints will be addressed by performing computations on Field Programmable Gate Array (FPGA) devices, traditional computer vision algorithms, and deep‑learning models. A high‑speed camera monitors the interaction between the melt pool and laser, producing data that must be processed within strict time limits. Three potential architectures are considered: 1) camera‑embedded FPGA, 2) capture card with a higher‑end FPGA, or 3) data transfer to system memory for CPU/GPU processing.

Key Responsibilities

• Develop image‑analysis algorithms targeting the camera’s embedded FPGA.
• Develop image‑analysis algorithms targeting the capture card’s FPGA.
• Develop image‑analysis algorithms for traditional computer CPUs and GPUs.
• Measure real‑time throughput for developed image‑analysis workflows.
• Create AI/Deep‑learning workflows for training models to analyze image sequences.

Qualifications

• 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.
• US citizenship preferred.

Equal Opportunity Employer

The National Institute of Standards and Technology is an equal opportunity employer and does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristics. Qualified individuals are provided access to all programs, benefits and activities on the basis of demonstrated ability, performance and merit.