Assistant Research Scientist (PREP0005086) - #Faculty

Johns Hopkins University; Gaithersburg (MD); On-site; USD 50,000 - 100,000; Full time

Job summary

Johns Hopkins University in Gaithersburg, MD, is seeking a PREP Research Associate to support collaboration with NIST on Physical AI research including ML, RL, and Foundation Models for Vision-Language Architectures. The role focuses on physics-based simulations and synthetic data generation to advance robust Physical AI systems.

Responsibilities include developing Physical AI applications, researching foundational model training for VLMs/VLA, and producing reports and weekly progress

Qualifications

• US Citizen Preferred
• Education: Engineering / Computer Science majors with Master's Degree or Ph.D, or in the final year of degree (e.g., Computer Science, Robotics, Mechanical Engineering or similar)
• Strong programming experience in Python and C+
• Experience in AI / Machine Learning frameworks (e.g., TensorFlow, PyTorch, etc.)
• Experience with developing and applying tools for Machine Learning, Reinforcement Learning, and Foundational Models for Vision-Language Models (VLM) and Vision-Language Action (VLA) architectures
• Experience in Synthetic data generation in and for NVIDIA IsaacSim, GR00T, and Cosmos environments
• Experience in Physics-based simulation engines (e.g., Gazebo, MuJoCo, Drake, etc.)
• Experience with version control software and workflow (e.g., Git, GitHub, GitLab, BitBucket, etc)
• Experience with Unix / Linux Operating systems
• Experience with ROS 2 on Linux systems
• Some experience in with CAD software (e.g., SolidWorks, OnShape, etc.)

Responsibilities

• Develop Physical AI applications using machine learning and reinforcement learning
• Research and develop Foundational model training for Vision-Language Models (VLMs) and Vision-Language Action (VLA) architectures
• Research and develop methods for synthetic data generation within platforms like NVIDIA IsaacSim / GR00T / Cosmos to conduct experiments to analyze system capabilities, and generate high-quality data to train robust Physical AI Systems
• Write reports and develop weekly presentations to explain the progress of the project
• Work Schedule: On-campus (Gaithersburg, MD), Full-Time (40 hrs / week)

Skills

Python

C++

AI/ML frameworks

ROS 2

Education

Engineering / CS advanced degree

Tools

Git

ROS 2

Gazebo

MuJoCo

Drake

IsaacSim

Job description

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: Physical AI Researcher

The work will entail: NIST is investigating the performance of commercial and custom AI systems (hardware and software) for Physical AI applications, specifically in machine learning, reinforcement learning, and foundation model training for Vision-Language Models (VLMs) and Vision-Language Action (VLA) architectures. The work will focus on leveraging physics-based simulations (e.g., Gazebo, MuJoCo, Drake) and synthetic data generation within platforms like NVIDIA IsaacSim / GR00T / Cosmos to conduct experiments, analyze system capabilities, and generate high-quality data to train robust Physical AI systems.

Key responsibilities will include but are not limited to:

• Develop Physical AI applications using machine learning and reinforcement learning.
• Research and develop Foundational model training for Vision-Language Models (VLMs) and Vision-Language Action (VLA) architectures.
• Research and develop methods for synthetic data generation within platforms like NVIDIA IsaacSim / GR00T / Cosmos to conduct experiments to analyze system capabilities, and generate high-quality data to train robust Physical AI Systems.
• Write reports and develop weekly presentations to explain the progress of the project
• Work Schedule: On-campus (Gaithersburg, MD), Full-Time (40 hrs / week)

Qualifications

• § US Citizen Preferred
• § Education: Engineering / Computer Science majors with Master's Degree or Ph.D, or in the final year of degree (e.g., Computer Science, Robotics, Mechanical Engineering or similar)
• § Strong programming experience in Python and C+
• § Experience in AI / Machine Learning frameworks (e.g., TensorFlow, PyTorch, etc.)
• § Experience with developing and applying tools for Machine Learning, Reinforcement Learning, and Foundational Models for Vision-Language Models (VLM) and Vision-Language Action (VLA) architectures
• § Experience in Synthetic data generation in and for NVIDIA IsaacSim, GR00T, and Cosmos environments
• § Experience in Physics-based simulation engines (e.g., Gazebo, MuJoCo, Drake, etc.)
• § Experience with version control software and workflow (e.g., Git, GitHub, GitLab, BitBucket, etc)
• § Experience with Unix / Linux Operating systems
• § Experience with ROS 2 on Linux systems
• § Some experience in with CAD software (e.g., SolidWorks, OnShape, etc.)

Salary: $50,000-$100,000 a year

Privacy Act Statement

Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)

Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) (https://www.nist.gov/iaao/academic-affairs-office/nist-professional-research-experience-program-prep) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.

PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.

Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.

Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.

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 here: https://hr.jhu.edu/benefits-worklife/.

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 characteristics. 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 or demographic characteristics that are irrelevant to the program involved.

Background Checks

After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre-employment background check including education verification. When deciding whether a candidate's conviction history is job-disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.

EEO is the Law

https://www.eeoc.gov/employees-job-applicants

Vaccine Requirements

Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. 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. We still require all faculty, staff, and students to receive the seasonal flu vaccine.

Exceptions to the seasonal flu vaccine or COVID-19 vaccine (for SOM) requirement(s) may be provided to individuals with sincerely held religious beliefs or medical conditions that preclude them from receiving the vaccine. Requests for an exception must be submitted to the JHU vaccination registry. For additional information, applicants for SOM positions should visit https://www.hopkinsmedicine.org/coronavirus/covid-19-vaccine/ and all other JHU applicants should visit https://covidinfo.jhu.edu/health-safety/covid-vaccination-information/.

The following additional vaccine requirements may apply, depending on your campus. Please contact the hiring department for more information.

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 candidates 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.

Job Type: Full Time