Internship: Generative Adversarial Networks (GANs) for Learning and Inference

Cambridge, Massachusetts, United States · CV · 1196 expand job description ↓


GANs (generative adversarial networks) and related methods (such as variational autoencoders) have generated much excitement for their ability to synthesize images and data that appear remarkably realistic. MERL is seeking a highly motivated intern to conduct original research in the area of generative adversarial networks with the goal of improving performance on real-world tasks. The successful candidate will collaborate with MERL researchers to design and implement new models, conduct experiments, and prepare results for publication. The ideal candidate would be a senior PhD student in computer vision with experience in GANs and related deep learning methods, as well as strong general knowledge in machine learning. Strong programming skills and previous experience coding GANs are expected. Duration: 3 months.

Research Area: Computer Vision

Contact: Tim Marks

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Are you qualified to apply for an internship at MERL? Qualified applicants for MERL internships are individuals who have or can obtain full authorization to work in the U.S. and do not require export licenses to receive information about the projects they will be exposed to at MERL. The U.S. government prohibits the release of information without an export license to citizens of several countries, including, without limitation, Cuba, Iran, North Korea, Sudan and Syria (Country Group E:1 of Part 740, Supplement 1, of the U.S. Export Administration Regulations).
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