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, UK. The position is funded by the European Commission through the MSCA Doctoral Network Endotrain (Grant No: 101227148) and coordinated by the University of Bergen, Norway. Supervisors: Dr Zuowei Wang
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Fundació Privada Institut d'Investigació Oncològica de Vall d'Hebron (VHIO) | Spain | about 1 hour ago
initiatives), providing access to a broad network and career advancement opportunities Applicants should include a full CV, letter of intent, brief (4-page approx) research proposal for the next 5 years, and
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and implementation of incentive mechanisms for sociotechnical and cyber-physical-human systems, with particular emphasis on smart mobility and urban transportation networks. In particular
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. The appointee will work on a project focused on next-generation communication and sensing technologies for enhancing safety and performance in intelligent networked systems. The appointee is expected to make
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pay and benefits, and a healthy work/life balance. Connections working at University of Michigan - Ann Arbor More Jobs from This Employer https://main.hercjobs.org/jobs/21805721/network-architect
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net zero. Project Description The green industrial futures depend on a sustainable and resilient resource supply chain to achieve the net zero goal. This project aims to develop a new approach to future
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flagship (https://fcai.fi ) and the ELLIS Institute Finland (https://www.ellisinstitute.fi ), part of the pan-European AI network of excellence (https://ellis.eu/members ). Significant high-performance
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perturbed. We will use complex networks to represent interactions within the climate system and to study its behaviour during tipping phases. Simulation outputs will guide the application of network
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to work with Florian Hollfelder at the Biochemistry Department of Cambridge University (https://hollfelder.bioc.cam.ac.uk/ ). The project is part of the Horizon Europe Eu Marie Curie Network MetaExplore
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Department/Location: Department of Biochemistry, Central Cambridge PhD Position - Marie Curie network ON-Tract: Protein engineering of enzymes: in vitro directed evolution and machine learning-based