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Field
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harmonized multi-model datasets of high-resolution decadal and multi-decadal scenario simulations for the three European target seas, and (ii) demonstrators of climate services at European Sea basin, coastal
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-of-the-art computational resources, enabling advanced simulations and modeling. Moreover, we actively collaborate with leading experts in laser diagnostics, automatic control, heat transfer, and life cycle
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in AI-modeling, Monte Carlo simulation, and coding. The successful candidate will work alongside a multidisciplinary team, leveraging artificial intelligence and computational methodologies to optimize
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-on experience in training large neural networks (generative models). Hands-on experience in medical image reconstruction. Preferred Qualifications: Proficiency in Python, C/C++, and Unix-like operating systems
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. Job description: - first-principle modeling and simulations of electrolytes - development of new machine learning strategies and quantum simulation approaches - application of specially developed
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: Using biogeochemical evolutionary models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life
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Applications are invited for a 2-year position in the field of CFD and modeling of heat pumps at the Department of Mechanical and Production Engineering, Aarhus University, Denmark. Expected start
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simulations to (i) minimize the discrepancies between measured and modelled historical ocean carbon sinks, (ii) elucidate key mechanisms driving BCP changes, and (iii) constrain the uncertainties in Earth
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Post-doctoral Position in AI Causal models for Synchrotron Anomaly Detection H/F This post-doctoral position is part of a collaboration between LIAD (Laboratory of Artificial Intelligence and Data
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team and participate in our vibrant research community here at CSIT. Project Title: Fault-tolerant Wireless Time Sensitive Networks This project builds on our ongoing work on modelling and simulating