Assistant Research Scientist (PREP0003758)

General Description Salary: $37.62 - $38.35 an hour PREP Research Associate 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 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. US Citizen Preferred. Salary Range The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University. Total Rewards Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found at Equal Opportunity Employer The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university 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 characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved. Background Checks The successful candidate(s) for this position will be subject to a pre-employment background check including education verification. EEO is the Law Vaccine Requirements Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the COVID and flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. For additional information, applicants for SOM positions should visit and all other JHU applicants should visit The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office. #J-18808-Ljbffr Johns Hopkins University