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intelligence. Our research spans computer vision, machine learning, and natural language processing, focusing on multimodal learning, data fusion, spatial-temporal modeling, and vision–language models. We study
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-augmented generation (RAG) approaches Systems and mathematical modeling of biological or complex systems Natural language processing and machine learning Data harmonization and integration Record of research
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Position Description Position Description The research group of Professor Mikaela Iacobelli in the Department of Mathematics at ETH Zurich invites applications for a two-year postdoctoral position
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, machine learning, generative AI and related fields as part of the DataSig II grant “High order mathematical and computational infrastructure for streamed data that enhance contemporary generative and large
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watermarks. Publishing research in leading journals and conferences in speech, audio, and machine learning, and contributing to open-source releases of software, trained models, and reproducible research
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following areas is desirable: collection and analysis of dense nodal seismic datasets, ambient noise tomography, high-performance computing, machine learning applications in observational seismology, and
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atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible computational workflows, collaborate with
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sensing, including Ultrasound and Hyperspectral Imaging (HSI), Artificial Intelligence (AI) and Tiny Machine Learning (TinyML). Duties As a Postdoctoral researcher you are expected to perform both
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investigate out-of-equilibrium dynamics in high-dimensional disordered systems (including models relevant to machine learning and optimization) by characterizing the fixed points (metastable states, attractors
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Postdoctoral position in Systems and Hardware Security The Computer Security Group is a research group in