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Would you like to work at the intersection of transportation, robotics and machine learning to design mixed fixed-flexible transport networks? Job description The increase of public transport usage
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is on analysing first-person descriptions of conscious experiences with the help of machine learning and large language models (LLMs) to identify, compare, and systematize different types of states of
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learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts. For example, we would like to be able
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order to develop advanced control, estimation, planning, learning and diagnostics strategies which are at the core of the intelligent autonomous systems of the future: Designing and realizing smart
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Become an EXPLORA-er to study how exploratory behavior impacts perception! And design multisensory EXPLORA kits with your team to show the world what light and materials can do. Job description Two
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theory, discrete optimization and machine learning. In this PhD position you will focus on strain-aware genome assembly, variant calling and strain abundance quantification for viruses, bacteria and yeasts
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machine learning solutions to optimize the component lifecycle directly contributing to a more circular economy. Information In the manufacturing landscape, determining whether a component should be
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, stringent layout design rules demand new design automation solutions beyond the actual state-of-the-art. The proposed work plan focuses on the thorough exploration of innovative generative machine learning
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Are you passionate about making public transportation and public space more accessible? Join the BRIDGE-XR project and design inclusive wayfinding systems using XR to help make urban travel
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unmanned aerial systems (UAS or drones), satellite imagery, and other spatial-temporal datasets. In addition to machine learning development, the candidate will be actively involved in the design and