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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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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a
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exists for researchers to design and improve animal tests. These limitations hinder the development of optimal experiments and incur cruel animal suffering and killing.The position is two years and you
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of research that has been developed at the Unit is the proposal and computational implementation of novel formulations for the conceptual design of mechanical components and structures via topology optimization
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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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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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students by the autumn, in addition to three faculty and two postdocs. Our group's research spans various facets of complexity theory, encompassing both combinatorial and logical perspectives. Key areas
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responsibilities of the successful candidate will be: Perform research in designing, synthesizing, and characterizing electrocatalysts for optimized amine-mediated CO₂ reduction. Perform mechanistic studies and
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topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks above, the postdoc can be involved in
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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