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Participate in a dedicated training plan For further information, please contact Prof. Marcus Völp at critix- Your profile Qualification: PhD in Computer Science Experience in dependable systems, real-time and
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to develop solutions with real world relevance and impact. This project will be carried out in close collaboration with researchers from the Division of Material and Computational Mechanics at IMS and the
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: PhD in social science, data science, computer science, information systems, environmental science, ecology, or related field. Demonstrated ability to conduct independent research, as evidenced by peer
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University of British Columbia | Northern British Columbia Fort Nelson, British Columbia | Canada | 3 months ago
experimentalists, cancer research scientists and biomedical engineers. Qualifications The candidate must hold a PhD in one of these disciplines: Mathematics, Numerical Analysis, Computational Mathematics
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. Qualifications: • A PhD in applied mathematics, statistics, electrical engineering or computational sciences completed within the past 5 years (or soon to be completed) • Experience in numerical analysis and
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. Applicants must have submitted their PhD thesis to the PhD evaluation committee when sending the application. Appointment is conditional on having successfully defended the PhD thesis. The candidate´s PhD
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plant architecture optimization, but new areas, particularly in molecular biology, immunology, and genomics, are welcome. For more information, see: navlakhalab.net. Position Requirements PhD in
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explore enabling technologies for 6G and beyond wireless networks. Applicants must hold a PhD degree in electrical/electronics engineering, telecommunications or related field. Other requirements include
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, treatment planning, and patient care. The research will involve data collection and preprocessing, model architecture design, pre-training and fine-tuning, evaluation and benchmarking, and model optimization
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Stanford’s Department of Computer Science and the Data Science team at Stanford Health Care. Our research spans both core methodological advancements (e.g., developing novel ML architectures and evaluation