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Field
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
of simulation, optimization, and policy modelling. You will also connect with TU Delft's strong internal network on climate action, particularly through the Climate Action Programme and its Climate Governance
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will provide fundamental insights that help optimize chemical recycling processes, bringing Europe one step closer to a truly circular plastics economy. This PhD project is part of a national research
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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
, optimization, and policy modelling. You will also connect with TU Delft's strong internal network on climate action, particularly through the Climate Action Programme and its Climate Governance theme. TU Delft
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Systems department. You'll collaborate with an interdisciplinary team working at the intersection of simulation, optimization, and policy modelling. You will also connect with TU Delft's strong internal
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antibodies) from individual serum samples. You will further develop and optimize these methods, with as special aim to enrich for antigen-specific antibodies. A secondary key objective is to improve
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each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In FlexMobility we propose a holistic approach to design
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; Modeling (using Gromacs and LAMMPS software packages and MARTINI-like upscaling) the filler-matrix interfaces to optimize thermal transport, e.g., by functionalization of the nanofiller surface; Simulate and
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environmental footprint.In this context, the optimization of material recovery from end-of-life vehicle scrap is challenged not only by the heterogeneous and evolving nature of this scrap, but also by the diverse
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developing intelligent algorithms that can support repair and remanufacturing decisions for sustainable manufacturing? As a PhD researcher, you will create innovative machine learning solutions to optimize
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Systems department. You'll collaborate with an interdisciplinary team working at the intersection of simulation, optimization, and policy modelling. You will also connect with TU Delft's strong internal