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machine learning for transport simulation. A core innovation involves Bayesian metamodeling techniques to construct fast surrogate models of the simulation space, enabling efficient scenario analysis
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. The objective of the position is to publish two papers in peer-reviewed journals. Your main tasks will include: Developing optimization frameworks for flexible demand asset, participating in the intraday
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Postdoc in development and testing of electrodes for liquid alkaline water electrolysis - DTU Energy
will be working with the overall objective of making active, durable and cost-effective electrodes for liquid alkaline electrolyzers for hydrogen production. Your primary tasks will be: Synthesis
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. The ideal candidate will demonstrate: Proven experience in thermodynamic modelling, thermo-economic analysis, and multi-objective optimization. Strong publication record in thermal conversion systems (e.g
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-objective optimization. Strong publication record in thermal conversion systems (e.g., Carnot batteries, heat pumps) and/or energy storage technologies. Proficiency with scientific tools such as EES, Modelica