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Are you passionate about advancing sustainable mobility solutions? Do you enjoy working at the intersection of artificial intelligence, optimization, and energy management? We invite applications
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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. The postdoctoral project will be focused on the design of optimized generation schemes for tailor-made electron beam and radiation sources in laser-produced plasmas. As a postdoctoral scientist, you are employed by
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environments ensure safe operations Our activities are primarily related to the development and application of numerical modelling (e.g. CFD, FEA, FSI, optimization, ML), but we are also involved in experiments
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from 3D-optimized end-walls provided by additive manufacturing (AM). The project outcome will solve the urgent need for CO2 reduction from air traffic. Research environment You will join the Fluid
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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of Electrical Engineering . You will be supervised by senior researchers with expertise in robotics, machine learning, automatic control, and optimization. The group leads and participates in numerous
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central role in streamlining and standardizing the design flow for quantum device fabrication. This includes implementing and improving design rule checks (DRC), optimizing and debugging code, and
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, design and characterization of quantum processors Development and optimization of nano-fabrication processes for large-scale devices Development of optimal control techniches to achieve fast and high
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on building the next generation of quantum processors based on superconducting circuits. To achieve this ambitiuous goal, we have a variety of projects related to: Development and optimization of nano