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Field
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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depends on the background of a suitable candidate. The main topics of the group in the past few years were generative modeling, 3D reconstruction, image-editing, and deep learning using 3D data. More
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the correctness, robustness and reliability of deep neural networks and AI-enabled software systems. Job Responsibilities: Conduct research in adversarial machine learning, AI security and the robustness of deep
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methods and deep learning to enable scientific reasoning. Develop software prototypes for automated research workflows that integrate autonomous discovery pipelines with modern deep learning architectures
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of deep neural networks and AI-enabled systems. Explore techniques such as abstraction, invariant learning, convex approximation, symbolic analysis and high-dimensional geometric analysis to improve
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, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep Learning Video Understanding Multimodal AI Excellent programming skills in
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operation and maintenance of equipment Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer
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should possess: PhD/Ms/BSc in Computer Science, Artificial Intelligence, Electrical Engineering, or a related discipline. Strong research background in one or more of: Computer Vision Machine Learning Deep
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new theory, models and algorithms in the areas of computer aided design, geometric modeling, deep learning, LLMs, etc. Develop and implement algorithms and prototype tools for 3D content generation
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Models. Experience with deep learning frameworks such as PyTorch or TensorFlow. Proficiency in programming languages including C/C++, Python, Java, and Go. Familiarity with Digital Content Forensics