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training in computational chemistry and computer-aided drug design. Group members will not only have the opportunities to work with cutting-edge resources in a collaborative environment but also to co-work
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can significantly improve the treatment and outcome of oncological patients. Project background You will contribute to the design and implementation of machine-learning-based sparse 3D image
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, electrical engineering and computer science to design highly efficient and sensitive imaging and inference approaches to help guide diagnosis and treatment in cardiovascular patients. Project background
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interventions with a patient’s clinical state, lesion characteristics, and multimodal biomarkers to optimize therapeutic effectiveness, across the pathway of care. This research axis is embedded in the CEREBRIS
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. The work will contribute to building an open, scalable, and modern approach to cluster management for large-scale High Performance Computing (HPC) systems. The main objective is to design, develop, integrate
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hardware and firmware issues Optimise power consumption, communication reliability and embedded system performance Support electronics testing, validation and design verification Help establish engineering
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reliable methods to detect reliable traces of life (biosignatures), whether through remote sensing or direct onsite measurements, requires significant innovation. These challenges demand close collaboration
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an emphasis on environmentally and economically efficient design and operations. Job description You will support the ESA Chair with general research-related tasks relating to ongoing projects, e.g. literature
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-docs. Our mission is to foster interdisciplinary AI research and pave the way from science to society. Project background As AI for Science Engineer you build the frontier AI systems that help
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, ensuring that responsibilities and handovers are clear. Plan feedback and evaluation logistics for learners, trainers and program staff, and ensure that operational findings are converted into agreed