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. For more details on benefits, please see: https://hr.utexas.edu/prospective/benefits and https://hr.utexas.edu/current/services/my-total-rewards . This position is eligible for a hybrid Flexible Work
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to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/ For eligible successful applicants, the studentships comprises
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infrastructures in power grids and ensure their reliable and sustainable operations. The project combines cutting-edge cybersecurity and network technologies, e.g., programmable intrusion detection and network
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creating planning tools and strategies for grid reinforcement and connection requirements at distribution and transmission levels. Collaborate with industry to ensure solutions meet reliability and power
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Veterinärmedizinische Universität Wien (University of Veterinary Medicine Vienna) | Austria | 2 months ago
demonstrate experience in these fields, have strong team skills as well as strong personality, reliability and willingness to share knowledge and the ability to work cooperatively with all services
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to apply E-mail recruitment@biomed.cas.cz Requirements Research FieldBiological sciences » BiologyEducation LevelPhD or equivalent Skills/Qualifications PhD in ecology, limnology, microbiology, or a related
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application! We are now looking for a PhD student in infrainformatics with focus on semantic and goal-oriented communication specialized on cloud-assisted artificial intelligence and control systems. Your work
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early-stage information into reliable, timely insights via user-ready dashboards, prototypes and pilot deployments, to reduce manual effort and error. Key objectives include building secure data
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— to ensure reliable patient flow and broader clinical impact. Advance key programs in spine, neuro-oncology, functional neurosurgery, and pediatrics with clear plans for growth and quality. Create a cohesive
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. Stefanos Zafeiriou can be found at https://wp.doc.ic.ac.uk/szafeiri/ . Research Associate: A PhD (or be close to completion) in an area pertinent to the subject area, i.e. computer vision, machine learning