Senior Research Scientist; PREP

Salary

$78,000-$85,000 a year

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). The PREP program enables research staff to collaborate with academic institutions on scientific projects. Individuals in this role will perform technical work supporting the collaboration’s scientific research.

Reference Material creation to Calibrate AI Solutions across labs

• Design and training of convolutional neural networks for cell segmentation, division detection, and label‑free cell viability assessment across imaging modalities.
• Design architectures for the transfer of AI models across labs.
• Develop new AI architectures for meniscus removal using image‑to‑image regression networks.
• Create a generalized meniscus removal solution that works across image content.
• Create a model that predicts an image quality metric based on existing blur metrics and compare it with a regular convolutional neural network.
• Produce high‑quality publications and present findings at internal and external meetings and conferences.
• Carry out statistical analyses and interpret results.
• Compile and clean large datasets.
• Determine methods to analyze complex data for validation.
• Develop innovative methods and research directions that support project goals.
• Co‑author reports on analysis results.
• Present results at internal meetings and occasional external stakeholder meetings.
• Ensure results, protocols, datasets, and documentation are archived or transmitted to the larger organization.

• US citizenship preferred.
• PhD in Computer Science (or related field) 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 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 any other legally protected characteristics.