Postdoctoral Position in AI for Cell Reference Materials (Computer Vision, Bioengineering) George Washington University in United States

The George Washington University, in collaboration with the National Institute of Standards and Technology (NIST), is seeking a Post-Doctoral Fellow for a cutting-edge project in the Information Technology Lab (ITL) located in Gaithersburg, MD. The position is part of the IMS project, "Distributed Manufacturing of First-In-Class NIST Traceable Active Cell Reference Materials," and aims to address the reproducibility crisis in biotechnology by standardizing AI-driven cell analysis.

The successful candidate will design and train advanced Convolutional Neural Networks (CNNs) and Vision Transformers for cell segmentation, division detection, and label-free viability assessment. A key responsibility is to create reference materials that enable calibration and transfer of AI solutions across different laboratories, ensuring accuracy and reproducibility. The role involves architecture design for AI models where training data is limited, cross-lab calibration, and the development of deployable software using PyTorch for complex cell image analysis.

Applicants should have a PhD in Computer Science, with at least three years of relevant experience, and demonstrate mastery in PyTorch/Python, Vision Transformers, and CNNs. Strong software development skills and a proven ability to communicate complex data to multidisciplinary audiences are essential. The position offers the opportunity to produce high-quality publications and present at leading AI and bioengineering conferences.

This postdoctoral fellowship is based at the NIST campus in Gaithersburg, MD, and is ideal for candidates interested in artificial intelligence, computer vision, deep learning, bioengineering, and the development of standardized reference materials for biotechnology. For more information and to apply, follow the provided application link.