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Scientific Computing focuses on research in programming paradigms, languages, compilers, and software and hardware infrastructures for scientific computing to support users in the process of solving
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participate in research, teaching & administration, which means: You develop computational tools for designing optimal synthetic communities and modularized production units within microbes. You create software
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(quantitative research methods and advanced proficiency in statistical software such as Mplus, R, etc.) • Teaching experience/experience in e-learning • Experience in student supervision • Excellent
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computational software development. You enjoy working in a team where you contribute your expertise and skill set to deliver an ambitious research vision and where you can contribute to the training of PhD and
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to tackle this ambitious challenge by developing and applying new software tools that combine machine learning methodology, electronic structure theory, and molecular dynamics methodology to simulate
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that aims to tackle this ambitious challenge by developing and applying new software tools that combine machine learning methodology, electronic structure theory, and molecular dynamics methodology
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knowledge of research practice, as well as a broad understanding of how research operates and how data and software underpin reproducible research Experience with designing and delivering training Very good
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develop software to process meteorological input data to the model, as well as software for the analysis of model output. One example is the software FLEXINVERT, which is used for inverse modelling
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Expertise in 4Pi microscopy hardware and software General Expectations: Above-average MA or equivalent in a field of study relevant for the respective position. Excellent academic and study record (e.g. FÖP
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quantum mechanics-based methods for the description of condensed matter systems, including the successful software package VASP (Vienna ab-initio Simulation Package). Currently, the group consists of two