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, ideally in Python, with demonstrated experience in applying them in complex research or development projects Basic knowledge in Machine Learning, ideally supported by initial hands-on experience Experience
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this knowledge, develop them as minimally invasive neural devices. Specifically, we aim to develop a toolbox of nanomaterials to study and learn from, looking at e.g. how nanoelectrode size and shape affects
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smart grid). While there has been tremendous progress in formal verification of cyber-physical systems, existing approaches still require expert knowledge. The main goal of this project is to develop
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-cell structural analysis of actin assembly and force generation Your profile: - Excellent BSc in biology, physics, biochemistry, bioinformatics, or related field of science - Knowledge/experience with EM
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engineering and machine learning skills Hands-on mentality with first practical experience in developing innovative software Inquisitive and passionate about research and knowledge transfer Independent
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. Essential skills include a sound understanding of Linux and related systems, software development standards, and hardware management. Additional beneficial skills include a theoretical knowledge of and
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about research and knowledge transfer Independent, creative, and committed way of working Ability to think conceptually and analytically At least basic knowledge of energy technology and systems Very good
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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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diagnosis, and knowledge of the operation of helicopter systems. • Confident handling of Python and common data science tools. • Knowledge of high-performance computing and machine learning. • Fluency in
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fundamental understanding of NanoLPC from multiscale experimentation and simulation aspects, not only to enhance the knowledge of LPC throughout different scales but also to support a range of emerging