Senior Research Scientist (PREP0004779)

General Description Salary: $78,000-$85,000 a year PREP Research Associate This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration’s scientific research. Research Title Reference Material creation to Calibrate AI Solutions across labs Work Overview ITL’s role in the IMS project “Distributed Manufacturing of First‑In‑Class NIST Traceable Active Cell Reference Materials” involves the following tasks: (1) the design and training of convolutional neural networks (CNN) for cell segmentation, cell division detection across time, and label‑free cell viability assessment under different imaging modalities, and (2) the design of reference materials with which to transfer AI models across labs. Our success depends upon the availability of highly skilled domain experts. We are challenged with difficult tasks that require not only expertise in running different types of CNNs, but also in designing new architectures for applications where training data is scarce but high accuracy is paramount. Key Responsibilities Develop new AI architectures for meniscus removal using image‑to‑image regression networks. Create a solution that generalizes meniscus removal regardless of content imaged. Create a model that predicts an image quality metric based on existing blur metrics and compare that solution with a regular convolutional neural network. Produce high‑quality publications based on research and results presented at internal and external meetings and conferences. Carry out statistical analyses and interpretation of results. Compile and clean large datasets. Determine methods to analyze complex data for validation. Develop innovative methods and research directions that support goals. Co‑author reports on results of analyses. Present results at internal meetings and occasional meetings with external stakeholders. Ensure that results, protocols, datasets, and documentation have been archived or otherwise transmitted to the larger organization. Qualifications US citizenship is preferred. PhD in Computer Science with 3 or more years of relevant experience. Expertise in PyTorch/Python and state‑of‑the‑art AI models such as vision transformers and advanced CNNs. Ability to build deployable complex software solutions for cell image analysis. Strong oral and written communication skills and strong presentation skills. U.S. citizenship preferred. Equal Opportunity Employer The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. 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. EEO is the Law #J-18808-Ljbffr The American Ceramic Society