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the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description [Background of the recruitment and description
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Postdoctoral Researchers – Biochar, Syngas, Green Hydrogen & Net-Zero Heat Systems Specialization: Advanced Electrochemistry, Integrated Spectroscopy & Net-Zero Applications Locations: IAAM Net
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planned work, including one of the UK’s only 7 Tesla MRI systems located inside a hospital environment, state-of-the-art engineering and physics laboratories, high-performance computing, and industry
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: 2023809 Carnegie Mellon University is a private, global research university that stands among the world's most renowned education institutions. With ground-breaking brain science, path-breaking performances
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to work in a vibrant research environment with faculty and collaborators across computer science, data science, design, and ethics, and to contribute to high-impact research that shapes the development
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for a second year, based on performance. Start date is negotiable, but the position is available immediately. Required Qualifications Ph.D. in Biology, Bioinformatics, Genomics, Population Genetics
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Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description The main responsibilities of the position include
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-Waals heterostructures. The research scope of the Research Unit also includes spin-wave physics, inverse-design magnonics, spintronics, millikelvin-temperature quantum physics, unconventional computing
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
management. Develop and validate computational models for monitoring and predicting infrastructure performance. Collaborate with faculty and researchers across SHORES. Disseminate research findings through
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Science, Computer Science, Applied Mathematics, Engineering and Physics. Additional Qualifications Expertise (or desire to work) in reduced order modeling, Causal inference and High Performance Computing