We seek a highly motivated intern to conduct original research in conditional diffusion models for computer vision tasks. We are interested in applications to various tasks including image editing, multimodal generation, and image-to-image translation. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The candidate should be a PhD student (or postdoc) in computer vision and machine learning with a strong publication record. Strong programming skills, experience developing and implementing new models in deep learning platforms such as PyTorch, and broad knowledge of machine learning and deep learning methods are expected. Previous experience in diffusion models is required.

MERL is seeking a highly motivated intern to conduct original research in estimating vital signs such as heart rate, heart rate variability, and blood pressure from video of a person. The successful candidate will use the latest methods in deep learning, computer vision, and signal processing to derive and implement new models, collect data, conduct experiments, and prepare results for publication, all in collaboration with MERL researchers. The candidate should be a PhD student in computer vision with a strong publication record and experience in computer vision, signal processing, machine learning, and health monitoring. Strong programming skills (Python, Pytorch, Matlab, etc.) are required.