PREP0004368 Cell Reference Materials Researcher

AI for Cell Reference Materials Researcher

Project Description:

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 may include, but are not limited to: 

• Developing new AI architectures for cell segmentation and cell division through time
• Creating custom built reference materials and measurement strategies to transfer the AI solutions between labs for specific cell-based assay experiments
• Produce high-quality publications based on research and results present at internal and external meetings and conferences

Desired Qualifications: 

• U.S. citizens preferred
• Ph.D. degree in Computer Science with 3 or more years of relevant experience
• Expertise in Pytorch/Python and state of the Art AI models like 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

Other Details:

• Full-time: the participant is expected to work 40 hours a week
• Location: the participant will work at the NIST Gaithersburg Campus.
• Duration: this is expected to be a one-year position. Extensions are sometimes granted depending on the availability of funds.