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-level GW+C implementation in the FHI-aims software package. Currently, this approach is limited to molecules; your task will be to adapt and expand it for application to 2D framework materials
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skills in one or more languages (Python, C/C++, or others) experience in mechanical testing profound knowledge of machine learning methods (e.g., neural networks, Gaussian processes, active learning
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for scientific work strong programming skills and experience in software projects excellent written and spoken English skills TUD strives to employ more women in academia and research. We therefore expressly
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#an exciting and varied job in a research centre with around 1,000 employees from more than 60 nations #a well-connected research campus (public transport bus) and best networking opportunities #individual
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genomic, gene expression and gene regulatory network data sets. We are looking for a highly motivated scientist to work in a dynamic and interdisciplinary academic team focusing on different aspects
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competitive salary in one of Germany’s most attractive research environments. TUD is one of eleven German Universities of Excellence and provides outstanding working, research, and networking possibilities