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an exceptional international team with expertise in all aspects of the project. Your tasks will include: • Preparation of different EO and in-situ datasets for training a machine learning model • Development of ML
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. Clinical studies have demonstrated that hereditary neuropathies can also involve muscle pathologies, complicate diagnosis and hamper therapy development. We have developed advanced in vitro cell models
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. Empa is a research institution of the ETH Domain. Empa's Laboratory of Biomimetic Membranes and Textiles is a pioneer in physics-based modeling at multiple scales. We bridge the virtual to the real world
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of quick clays. A novel combination of miniaturised thermal-hydro-mechanical experiments and particle level modelling will be pursued to unravel the unique mechanisms that make quick clays so hazardous and
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energy data lifecycle spans pre-construction (e.g., meteorological mast data, LiDAR data, wind climate and energy yield modelling, environmental impact assessment data), operational phases (e.g., SCADA
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or compromised IoT devices by analysing encrypted traffic patterns, focusing on metadata, flow characteristics, and timing rather than decrypting payloads. The core challenge is creating features and models
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with host bacteria during infections, particularly focusing on the use of E. coli and its related phages as model organisms. However, the results may be applied in pathogenic bacteria related to E. coli
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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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/or modelling is essential. Experience in machine learning, computer vision, and computer programming is desirable. In addition, applicants should be highly motivated, able to work independently, as
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requirements. The assessor will conclude whether each applicant is qualified and, if so, for which of the two models. The assessed applicants will have the opportunity to comment on their assessment. You can