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problems. The mission of this consortium is to realize a new revenue model in the textile value chain, by scaling up and strengthening the (business/government/NGO) activities around sorting and recycling
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, engineering, informatics, or a related field. Proven experience in energy system modeling, preferably with PyPSA or a similar framework. A strong understanding of energy system modeling and optimization
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Organisation Job description For the National Growth Fund (NGF) project “Groeien met Groen Staal” (GGS), a PhD position for the period of 4 years is available in the context of modelling green steel
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Engineering, Computational Physics, Materials Science or a related discipline is required, with experience in atomistic modelling of materials and machine learning. Experience in atomistic modelling (molecular
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described in the project overview. Owing to the current composition of the project team, there will be a mild preference for candidates opting for project 2 on “Models and machine learning”. An explanation
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PhD in Data-Driven Modeling of Homogeneous Catalysts (1.0 FTE) (V25.0035) « Back to the overview Job description Among the most challenging to develop catalytic reactions are stereoselective
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energy system modelling is critical for reducing emissions, enhancing resilience, and integrating high shares of renewable energy sources. Such modelling provides essential tools for designing low-carbon
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properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and used to establish such a
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-year PhD program, you will join a collaborative research team applying cutting-edge methods from Experimental/Behavioral Economics alongside modern macroeconomic modelling techniques (e.g. DSGE). You'll
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to characterize the molecular properties of catalysts together with statistical methods to derive predictive models for selective catalysis. In a data-driven approach, an initial set of reactions is analyzed and