Internship: Visual Content Synthesis
DescriptionWe are looking for a highly motivated intern to work on developing deep learning algorithms for visual content generation. Successful candidate will collaborate with MERL researchers to design, analyze, and implement new algorithms, conduct experiments, and prepare results for publications. The candidate should have a strong background in computer vision and machine learning fundamentals. Prior experience and a good knowledge of the recent trends in deep learning methods is required. Familiarity with methods such as generative adversarial networks or variational autoencoders is a plus. The candidate should be comfortable implementing the developed algorithms in Python and should have prior experience working with frameworks such as Caffe/TensorFlow/Keras/Theano. The candidate is expected to be a PhD student in Computer Science, Electrical Engineering, or a related field, with relevant publication record. Interested candidates are encouraged to apply with their recent CV with a list of relevant publications and links to Github repositories (if any).
Research Area: Computer Vision
Contact: Anoop Cherian
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