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Field
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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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. optimization and machine learning techniques) to prepare ports, terminals, shipping companies, and other port actors for this important challenge. Your research will be part of the PortCall.Zero project - a five
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support each other. This necessitates a multidisciplinary approach bringing together optimization, machine learning and behavioral modeling methodologies. In the FlexMobility project we propose a holistic
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candidate will be an integral part of the prestigious ERC Consolidator Grant, THERMODON on harnessing the unique capabilities of ONNs to solve combinatorial optimization problems. ONNs, inspired by
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increasing the attractiveness to the users, we need innovative designs where fixed and flexible services support each other. This necessitates a multidisciplinary approach bringing together optimization
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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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ODTÜ-GÜNAM, and contribute to pilot demonstrations in Romania, Türkiye, and Spain. The project provides a good mix of hands-on lab development, modelling, and system-level optimization in one of Europe’s
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organisms have been lacking. You will build on our recently developed single-cell ribosome profiling methods for C. elegans and further optimize them to apply to the early embryo. With this approach, you will
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poor precision. Consequently, quantitative MRI is not used routinely in cancer care. If we can improve the image quality of quantitative MRI, it can be used in clinical routine to select the optimal