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the synchrotron-based imaging technique Dark-Field X-ray Microscopy and together we utilize it to visualize the evolution of internal structures in metals during plastic deformation, i.e. changes in shape due
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electron microscopy (TEM), and X-ray photoelectron spectroscopy (XPS) You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's
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theoretical models to describe the dynamics of quantum light sources, with the goal of understanding their behavior and improve their performance. You will work in close collaboration with the experimental team
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other duties, which are broadly in line with the above duties and responsibilities. Where to apply E-mail reunatech@rwth-aachen.de Requirements Research FieldEngineering » Civil engineeringEducation
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directions will be pursued to enhance column generation using machine learning. The first line of research focuses on improving scalability by using Graph Neural Networks to identify and eliminate non
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may be required to undertake other duties, which are broadly in line with the above duties and responsibilities. Where to apply E-mail reunatech@rwth-aachen.de Requirements Research FieldEngineering
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related field Documented metagenomics experience Experience with writing and running data analysis scripts in a command-line interface Solid programming experience in Python Experience with scripting and
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. This knowledge will support the designation of marine protected areas in line with the “30 by 30” conservation target. A central component of the project is the integration and analysis of diverse data sources
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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for the PhD education . Assessment The assessment of the applicants will be made by Assoc. Prof. Line Hagner Nielsen, Prof. Stephan Sylvest Keller, Dr. Signe Tandrup Schmidt and Dr. Gabriel Kristian Pedersen