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the application criteria in the application statement when you apply. Criteria Essential or desirable Stage(s) assessed at A PhD, or be close to completion, in natural language processing, machine learning
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in one or more of the following research areas is desirable: geometric numerical integration, structure preserving deep learning, stochastic differential equations, generative AI, numerical
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/Qualifications Skills in acoustics and audio. Prefereably skills in machine learning and deep learning. Specific Requirements Education in acoustics. Knowledge of acoustical measurement techniques, as
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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA
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of cryptographic implementations and hardware-security countermeasures. Experience with hardware reverse engineering, debugging interfaces, or firmware analysis. Experience with machine learning, deep learning
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methods for differential equations and scientific machine learning; geometric deep learning, manifold learning, equivariant methods, high-dimensional geometry, and structure-aware learning; and the
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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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, multimodal, and agentic AI, as well as foundation models, with a focus on geometric deep learning, large-scale knowledge graphs, and large language models. Fellows will also have the opportunity to apply
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program. Analyze and interpret remote sensing datasets (satellite, UAV, and/or LiDAR-derived) relevant to fire, fuels, and landscape-scale research questions. Develop and/or adapt machine learning and deep
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/nanoplastics, and other environmental compounds to assess their potential impacts on human health and the environment using machine learning (ML), deep learning (DL), and big data analytics. His lab is