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Field
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Consortium’s Science Ground Segment, providing algorithm and software development, participating in data quality assurance, and performing data processing. In addition, ENSCI supports the US research community
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recovery conditions in inverse problems with sparsity constraints and to design algorithms that leverage these conditions [1]. This PhD topic investigates this framework in the context of observing
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machine learning by designing and developing innovative models and algorithms. Key Responsibilities: Designing and conducting comprehensive research in artificial intelligence and machine learning, with a
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automated recovery algorithms, improving system resilience. Research Areas for Master’s and PhD Students AI-Enhanced Resource Forecasting and Optimization: Research Focus: Developing and testing ML algorithms
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balances fundamental scientific inquiry with practical innovation, requiring the researcher to develop novel algorithms that address complex temporal constraints, resource allocation, and decision-making
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Fields Institute Fellowship ID: FIELDS-FPDFQUANTUMALGORITHMS [#27996] Fellowship Title: Fields Postdoctoral Fellowship - Quantum Algorithms for Differential Equations Fellowship Type: Postdoctoral
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100%, Zurich, fixed-term The Swiss Seismological Service (SED) at ETH Zurich invites applications for a PhD position within a multi-year applied research project on the detection, localization and
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‑world adoption. Role Overview We are seeking a postdoctoral researcher to define and execute an ambitious research agenda at the intersection of generative AI and algorithm-hardware co‑design for next
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of industrial processes. In a joint effort of both institutes, the Department AI4Quantum – Machine Learning for Quantum Simulation and Computing and Thermal Energy and Process Engineering are looking for a PhD
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optimise deep learning–based models for the quality control and real-time assessment of concrete constituents within in-line production. Develop and train predictive algorithms based on hyperspectral imaging