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together researchers from TU/e, the University of Twente, and Maastricht University. Working closely with a PhD candidate and the project's supervisory team, you will design, train, and iteratively refine
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identify those with the highest potential for early adoption in space engineering; translate theoretical advances into algorithmic innovations, design principles and prototype tools that can be integrated
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the project. What you will do Conduct original and high-quality research in machine learning and computer vision; Develop novel algorithms for adapting and specialising visual foundation models; Publish
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; Develop novel algorithms for adapting and specialising visual foundation models; Publish research findings at leading machine learning and computer vision venues such as CVPR, ICCV, ECCV, NeurIPS, and ICLR
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estimates, and emission algorithms. The relevant processes at the individual vessel level can be modelled in detail, and their performance can be tracked in time and space. Corridor scale effects will be
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algorithms. The relevant processes at the individual vessel level can be modelled in detail, and their performance can be tracked in time and space. Corridor scale effects will be simulated by aggregating
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, algorithms and products: undertaking advanced research activities addressing major observational gaps and scientific priorities in EO. The research will cover a wide range of innovative topics and missions
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, analyse, and validate innovative numerical algorithms and mathematical frameworks for problems arising in materials, fundamental physics, dynamics, optimisation, control, uncertainty quantification, inverse
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(for example insect-eye–inspired motion detectors for planetary landing and insect-inspired navigation algorithms) to evolutionary and neuromorphic approaches to autonomous control, as well as soft-robotic