The U.S. Food and Drug Administration invites graduate student/postdoc applications for an open FDA-ORISE Research Fellow in Regulatory Science for Continual Learning Machine Learning Systems. 

 

Continual learning in machine learning is poised to bring changes to the speed at which the health care industry will adapt to the changes in patient management. Research in this area is still at a nascent stage with several recent research publications aiming towards solving the Plasticity‐Stability dilemma. This is a critical time for the agency to develop performance assessment strategies to evaluate the safety and effectiveness of these continual learning algorithms. In this project, our goal is to develop an evaluation framework for continual learning algorithms specifically for segmentation and classification tasks. The research fellow will play a key role in developing and evaluating AI/ML algorithms.

 

Ideal candidates have a strong background in the fundamentals and an eagerness to solve technical challenges systematically with experimental and/or computational approaches. In addition candidates should have:

• A Ph.D. or master’s degree (or degree in progress) in engineering, physics, computer science, mathematics, or a similar quantitative field.
• Studies in Engineering, Physics, Optics, Mathematics, Computer Science, Statistics or similar
• Developing and analyzing AI/ML methods (CNN, RNN, GAN, etc.)
• Programming with Python (including scientific stack: NumPy, SciPy, scikit‐learn, etc.), and deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with image segmentation, processing and data management

 

For more information – including details on how to submit your application – please download the flyer (PDF).

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