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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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solutions to PDEs . Your work will involve utilizing GPU code generators for matrix multiplication kernels and ensuring the software is usable in Python for downstream data analysis [2]. Collaboration is
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, or supervised/unsupervised learning depending on the available data) using spatial analysis and geographic machine learning tools (e.g., scikit-learn, PyTorch/TF + GeoPandas/Shapely) - Implementing a semantic
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dynamical systems methods and data-driven analysis is a plus We offer Your job with impact: Become part of ETH Zurich, which not only supports your professional development, but also actively contributes
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information storage. However, most DNA storage systems remain passive: data are written, archived, and read. This PhD project will help pioneer a new generation of dynamic DNA data storage systems capable not
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Microlocal analysis explores the classical/quantum correspondence in partial differential equations (PDEs). For example, the concept of symbol quantisation in the theory of pseudodifferential
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Quantum Fields, Information, and Next-Generation Cosmological Probes This PhD project will investigate theoretical aspects of quantum field theory in cosmological spacetimes, with a particular focus
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framework for underlying structures in high dimension such as underlying covariance structure, conditional dependency graphs etc. With the change in data-generating mechanism, these high-dimensional
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PhD Studentship: Efficient Long-Horizon Task Execution in Physical AI (deep learning, computer vision, robotics) Number of awards: 1 Award information: Fully funded PhD studentship covering Home
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characterization techniques such as XRD, XPS, SEM, or TEM. Experience in data analysis, scientific programming (e.g. Python), statistical experimental design, as well as data-driven research methods and