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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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of multivalent nanoparticle vaccines. The team was recently awarded an ERC Advanced Grant to determine the optimal combination of epitopes that elicits the highest level of protection. Within
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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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of hyperdimensional computing and vector symbolic architectures (VSA). As a Senior Research Engineer, you will: Implement, optimize, and run simulation code in Matlab and Python. Develop lab assignments for upcoming
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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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, including finite-element simulation and topological optimization of light guidance in HCFs, and numerical simulation of thermo- and fluid dynamics under fiber-drawing processes. Apart from the main tasks
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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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. Our research integrates expertise from machine learning, optimization, control theory, and network science, spanning diverse application domains such as energy systems, biomedical systems, material