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laser arrays Optimization and acceleration of existing simulation codes Parallel computing and high-performance computing (HPC) GPU acceleration, where appropriate Development of scalable numerical
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scientific imaging. The primary responsibility of this position is designing and implementing sparse algorithms for large-scale scientific and numerical computations. The successful candidate will pursue
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of atmospheric dynamics, process scale models, and numerical computation techniques Knowledge of data analysis Knowledge of using atmospheric and hydrological observational datasets, data assimilation techniques
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of experience within the field. Scientific and numerical programming in Python or R and knowledge of class ML methods and deep learning methods. Well versed in a variety of bioinformatic analyses, including Next
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modeling with an understanding of numerical methods and physical processes relevant to ocean circulation and dynamics. Experience with high-performance computing, parallel numerical models, large scientific
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the application deadline. Have a solid background in quantum computing and quantum algorithms, sufficient to conduct research on the topic. Have programming skills (e.g., Python) and experience with numerical
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field. Candidates should have expertise in several of the following areas: Scientific software development (C++, Julia, Rust, Python, or similar) Numerical methods and scientific computing. High
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responsible for developing and analysing numerical models that describe progressive damage in laminated composites, with a clear emphasis on transferring detailed fracture mechanisms to models that can be used
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At the Department of Mathematical Sciences, faculty of Engineering & Science, at Aalborg University, we are looking for a postdoctoral researcher to join our group working on numerical methods
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mechanics, numerical methods, materials or related areas. This may include lecturing and project supervision at bachelor and master level. You will take responsibility for planning and carrying out your