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23 Jan 2026 Job Information Organisation/Company ETH Zürich Research Field Computer science » Computer architecture Computer science » Programming Computer science » Other Engineering » Biomedical
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technologies such as IoT, big data, analytics, computer vision, cloud computing, and artificial intelligence (AI). IoT devices help in data collection. Sensors plugged in tractors and trucks as well as in fields
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of the project is to develop and operate a tailored, near-real-time geodetic monitoring approach that provides reliable, transparent, and interpretable 3D surface displacement estimates. The research will focus
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simulation environment. The chosen code will be then adapted and tuned for the purpose of estimating radiological impact assessments of accidental releases from LFR-SMRs. A large set of simulations for short
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, advanced high-parameter flow-cytometry, as well as murine models and human organoid technology to investigate mechanisms of longevity of immunological T and B cell memory. A strong interest in quantitative
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parameters Development of learning rules considering the strong non-linearities of the neurons Identify suitable application task in the field of geolocation and optimize network and learning rules accordingly
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collected by moored probes, underwater gliders and micro-AUVs and shipborne sampling. Furthermore, parameters describing atmospheric variability and riverine inputs will be included in the analysis to better
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accurate Reactor Kinetics parameters for such models. This research will quantify how different modelling choices affect key neutron-physics and safety-relevant Figures of Merit and, in doing so, establish a
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integration of simulation and AI-based analysis. An analytical Monte Carlo-inspired simulator will optimize system geometry and acquisition parameters, support sensitivity studies, and serve as a forward
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on neurophysiology and behavior are typically small in size, the technique has the advantage to be very flexible in terms of application sites and time courses of the applied currents, leading to large parameter