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well as market and organization considerations. Education: Ph.D. in machine learning, computer science, engineering, science or related technical discipline. Experience: Expertise in developing and training AI
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FWO-UGent funded bioinformatics postdocs: Unveiling the significance of gene loss in plant evolution
environment Access to state-of-the-art tools and computational infrastructure, including CPU/GPU clusters Opportunity to contribute to cutting-edge research in plant evolution and genomics Support
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prioritize work while meeting multiple deadlines. Ability to communicate effectively in both oral and written form. Skill in using analytical software tools, data analysis methods, and other computer
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electricity prices with focus on Nordic electricity market including implementation, test and validation at the DTU Risø HPP facility (possibly in a GPU computing infrastructure) Aid the implementation of IEA
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Qualifications: Experience in real-time simulation hardware like Opal-RT and RTDS. Experience with software development. Experience with use of GPUs, multi-core CPUs, advanced computing (e.g., QPUs). Excellent
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multiple projects lead by the graduate students in the group and co-advise the graduate students. The candidate is expected to publish and present research findings in the computer science research
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
of data scientists/clinicians and working with unique datasets from multiple academic medical centers (e.g. UNC, UCSF, Mayo Clinic, Memorial Sloan Kettering, etc). Lab dedicated GPU workstations/servers and