Postdoctoral Fellow; PREP

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.

Reference Material creation to Calibrate AI Solutions across labs

ITL's role in the IMS project "Distributed Manufacturing of First-In-Class NIST Traceable Active Cell Reference Materials" involves the following tasks: (1) designing and training convolutional neural networks (CNN) for cell segmentation, cell division detection across time, and label‑free cell viability assessment under different imaging modalities, and (2) designing reference materials to transfer AI models across labs.

• Develop new AI architectures for cell segmentation and cell division through time.
• Create custom reference materials and measurement strategies to transfer AI solutions between labs for specific cell‑based assay experiments.
• Produce high‑quality publications and present research findings at internal and external meetings and conferences.

• U.S. citizenship preferred.
• A 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 and presentation skills.

The Johns Hopkins University is committed to equal opportunity 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.