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are proficiency in Python, deep learning frameworks such as Keras, PyTorch, TensorFlow, or other related software stacks, and a solid background in machine learning, cybersecurity, or AI robotics, and the ability
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generative AI methods such as GANs, VAEs, transformers, or foundation models (LLMs, TSFMs). Ability to design and conduct computational experiments, including model training and evaluation. Experience with
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. The successful candidate will have a doctoral degree in electrical engineering, physics, computer science, or applied mathematics, and superb computer programming skills. Recommended skills include an advanced
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, fined tuned for zooming in on machine spatial reasoning, is within the scope of this project. Developing efficient algorithms for converting computer simulations of a system in a complex environment (e.g
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, fined tuned for zooming in on machine spatial reasoning, is within the scope of this project. Developing efficient algorithms for converting computer simulations of a system in a complex environment (e.g
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of faculty at SUNY Polytechnic Institute and the University of South Florida, consisting of mathematicians, physicists, computer scientists, and engineers investigating applications of deep learning