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continuous improvement of hardware lifecycle programs, including PC as a Service (PCaaS), departmental purchasing models, and special-purpose computing environments. The incumbent applies advanced technical
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-, ground-, and simulation-based data on the landscape water balance with data analytics to understand how variations in connectivity influence hydrograph characteristics, e.g. flood peaks and drought
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: MSc or equivalent in the field of aerospace engineering or similar Solid knowledge of Computer Science and Informatics (simulation, optimisation and modelling tools; surrogate modelling, statistics and
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combining wave modelling, field observations, remote sensing, advanced mathematical methods and AI, the research will quantify spatial patterns of wave set-up, its statistical distributions and co-occurrence
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experience in computational systems modeling, simulation, and analytics; OR Master's degree in computational biology, systems biology, bioinformatics, biological engineering, biophysics, or related field plus
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attention to phenomena dependent on strain rate, temperature, thermal history, and microstructure; elasto-viscoplastic and micromechanical constitutive modeling, developed in academic and/or industrial
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to weather patterns and extreme events. Despite their importance, critical controlling processes remain poorly understood, underscoring the urgent need to improve Earth system modeling. Significant
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clusters versus sparse stellar associations), assuming a variety of different delivery mechanisms (supernovae, stellar winds). We will use these yields to model the contribution of 26-Al and 60-Fe the long
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challenging for classical computing architectures. Some of your responsibilities will include: Design and develop mixed-signal circuits for implementing ONNs. Modeling, simulate and benchmark different
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analog circuits for implementing ONNs for computing. Modeling, simulate and benchmark different computing tasks such as sensor data processing. Explore ONN implementation topology and its energy efficiency