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interested in working at the boundaries of several research domains Master's degree in computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta
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“Light- versus electron-induced spin-state switching of complexes on insulating layers” within the Priority Programme SPP 2491 “Interactive Spin-State Switching” This DFG-funded project aims
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to work in a team and in a research network • Computer programming experience • Knowledge in electronics • Experience in the field of optics and quantum optics is desirable We offer: • A truly unique
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-edge Machine Learning applications on the Exascale computer JUPITER. Your work will include: Developing, implementing, and refining ML techniques suited for the largest scale Parallelizing model training
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(MHH). The project is funded by the Wissenschaftsräume programme of the state of Lower Saxony and the Volkswagen Foundation. Your tasks will include: Design the physical intervention component of the app
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identification of spider mite infestation foci and needs-based beneficial insect application in outdoor cucumber cultivation’, which is funded by the BMBF within the funding programme KMU-innovativ: Bioökonomie
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that are technically well-grounded and at the same time represent stakeholder preferences. The integrated Research Training Group (RTG) will provide doctoral researchers with an attractive qualification program, foster
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Engineering (ISSE) is one of the two computer science institutes at Clausthal University of Technology and is home to several research groups. You can find more information about the ISSE Institute on our
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in inorganic synthesis and/or Schlenk-line preparations Experience with scientific programming (e.g., MATLAB, LabView) is advantageous Experience performing quantum chemistry computations (e.g., DFT