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English PhD Research Fellow in Machine Learning and Statistics Apply for this job See advertisement About the position Integreat - the Norwegian Centre for Knowledge-driven Machine Learning
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description languages. Develop and optimize EDA workflows for processor and accelerator design, verification, and physical implementation using open-source tools. Explore architecture-algorithm co-design for
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for one year and may be extended, subjected to performance and availability of research funding. Key Responsibilities: Develop state-of-the-art and innovative models and algorithms to improve port and
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surfaces. (iii) Optimize and enhance the computational algorithm by introducing a patterned spintronic THz emitter array to resolve the two-dimensional object image from the data set in real-time
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algorithms for digital health and AI-driven research projects. Lead technical innovation by exploring and implementing emerging AI methodologies. Support data platform development and retrospective data
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applications for a Postdoctoral Fellow to join an international research team on the Marsden Fund project Scalable Bayesian Algorithms for Multi-Physics Inverse Problems with High-Level Representations
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data analytics; Development of marine geophysical survey and machine learning algorithms; Process geophysical/geomechanical data and analyze the data using machine learning; Conduct research, supervise
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at least one of the following fields: approximation of neural networks, convergence of Langevin/MC sampling, analysis and algorithm design of interacting particle systems, operator learning, regularity
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Research Fellow (Software, AI & Autonomous Systems) Required Qualifications PhD in Robotics, Computer Science, Artificial Intelligence, Electrical, Computer Engineering, or related disciplines. Key
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. The Role Faculty of Environment, Science and Economy The successful applicant will contribute to the project NATALIE by developing AI algorithms that integrate data from various sources to better understand