Computer Vision PhD Intern (Summer 2026)

Benefits

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

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Remote From the posting source

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About this role

Computer Vision PhD Intern (Summer 2026) Global Remote | Remote WHO WE ARE. Reality Defender is an award-winning cybersecurity company helping enterprises and governments detect deepfakes and AI-generated media. Utilizing a patented multi-model approach, Reality Defender is robust against the bleeding edge of generative platforms producing video, audio, imagery, and text media. Reality Defender's API-first deepfake detection platform empowers teams and developers alike to identify fraud, disinformation campaigns, and harmful deepfakes in real time. Backed by world class investors including DCVC, Illuminate Financial, Y Combinator, Booz Allen Hamilton, IBM, Accenture, Rackhouse, and Argon VC, Reality Defender works with leading enterprise clients, financial institutions, and governments in order to ensure AI-generated media is not used for malicious purposes. Youtube: Reality Defender Wins RSA Most Innovative Startup https://www.youtube.com/watch?v=TKOZmwyNUNM THE COMPUTER VISION INTERNSHIP. This 3-month internship is designed for current PhD students and candidates to partner with Reality Defender's AI team to generate cutting-edge research and publish peer-reviewed papers. Your primary collaborator will be Jacob Seidman https://www.linkedin.com/in/jacob-seidman/, who will guide and advise your efforts within deepfake image and video detection. This internship can be performed remotely, although you're welcome to work from our HQ in New York City. WHAT YOU'LL DO. - Investigate new methods for generative image/video detection. - Collaborate with researchers in the team. - Perform research of deepfake image/video detection. - Write up results of research for internal reports and submission to academic journals/workshops. - Independently implement and evaluate ideas on modern deep learning stack - Python, PyTorch, and GPU-enabled

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