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-edge generative and predictive methods for materials discovery, we offer an excellent opportunity to advance your research. We are seeking a highly motivated and talented postdoctoral researcher to join
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potential for exploiting temperature gradients for producing electricity and predict their long-term performance under real operating conditions. The project also includes modeling of heat transfer and
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predictive framework linking genomic data to extinction risk, working at the interface of evolutionary genomics, simulation modelling, and machine learning. By integrating forward-in-time simulations, real
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execution time (WCET). The postdoc position focuses on compiler support for WCET analysis for time-predictable architectures such as Patmos/T-CREST. Furthermore, it is expected to join the development of a
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protein design tools to generate and prioritize inhibitor candidates with high predicted binding and selectivity. These designs will then be experimentally validated through a combination of affinity
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-of-the-art practical engineering models for predicting sand and particle transport struggle with the cross-shore processes (perpendicular to the beach), and they even have difficulties predicting the sign
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systems Strong skills in data-driven analysis and modelling, simulation, control, and validation Familiar with modeling of PtX and storage technologies, model predictive control, machine learning
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assessment models and evaluate the nutritional quality of foods. Build risk-benefit assessment models to quantify and predict the health impacts of new food products. A central case study will explore
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, through developing predictive models and new experimental methods and instrumentation, to design creative and cost effective CO2 trapping processes. The need is urgent, the task is challenging and a
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/or high-temperature heat pumps based on power cycles. Design thermal and/or thermochemical energy storage systems. Implementing and validating advanced thermodynamic models for performance prediction