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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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++, Java, Julia, or other competent languages. A good record of publications in reputable peer-reviewed journals in maritime transport, logistics management, machine learning, deep learning, and optimization
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computing environments and GPU computing. Proven experience in weather and climate models development and applications. Experience in machine learning, deep learning, or AI applications for atmospheric
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related field). Decent programming skills, especially in Python or JAX. Familiarity with finance theory (asset pricing, derivative pricing, risk management etc.). Familiarity with machine learning or deep
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system model new module integration, scenario simulations, and prognostics analyses Physics-informed deep learning/hybrid modeling/reasoning AI algorithm development and optimization Job Requirements: A
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apply machine learning and deep learning models (e.g., graph neural networks, generative models, transfer learning) for materials property prediction, interpretation, and inverse design. Perform high
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Post Quantum Cryptography (PQC), Homomorphic Encryption, Secure Computation. Experience with deep learning frameworks such as PyTorch or TensorFlow. Proficiency in programming languages, e.g. C/C
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, logistics management, machine learning, deep learning, and optimization; Proficient in written and spoken English - essential for data analysis and communication with stakeholders Interpersonal skills with
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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
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. Willingness to support project reporting and milestone reviews. Hard skills Strong programming skills in Python and deep learning frameworks such as PyTorch or TensorFlow. Experience in autonomous navigation