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, catalysis and/or surface science. For Topic 4, candidates must have documented skills within computational modelling of atomistic processes. Experience in scientific programming, e.g. using Python, is
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to career stage Excellent written and spoken English Programming skills (preferably Python) and experience with optimization frameworks will be considered an advantage Experience with infrastructure modelling
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design for resource allocation or distributed systems Solid mathematical and analytical skills. Experience in scientific programming (e.g., Python, MATLAB, or similar). Demonstrated ability to publish
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Programming skills (preferably Python) will be considered an advantage. Experience with infrastructure economics, carbon markets, or large-scale energy infrastructure planning will be considered an advantage
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research area: Python or C#, robotics, additive manufacturing, finite element analysis, or computational fluid dynamics. Experience in teaching and co-supervising thesis students at university level
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Andres Masegosa (arma@cs.aau.dk), Department of Computer Science. (please see: https://andresmasegosa.github.io/ . The project’s domain PI is Professor Jamal Jokar Arsanjani (jja@plan.aau.dk), Department
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Multiphysics, MATLAB, or Python Familiarity with device-level simulations and multi-physics approaches Self-motivated and able to work independently while contributing to a collaborative research environment
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(https://www.classique.aau.dk). CLASSIQUE will address a suite of fresh research challenges defined by the intersection of digital applications that have real-time requirements and quantum resources
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the following areas. You have a background in tissue-based molecular research and experience with tissue sectioning and the generation and analysis of spatial molecular data. Programming expertise in Python and R
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systems, integrated sensing and communication, and theoretical modeling of 6G systems Solid mathematical background and significant experience in scientific computing programming (MATLAB, Python, C/C