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models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
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, modelling and simulation of photonic systems, sensor systems, signal processing and device manufacturing, development of machine learning algorithms, and design of optical communication networks or power
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Research Back Profile Areas Cluster of Excellence CMFI Cluster of Excellence GreenRobust Cluster of Excellence HUMAN ORIGINS Cluster of Excellence iFIT Cluster of Excellence Machine Learning Cluster
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. Specifically, the PhD candidate is expected to contribute corpora preparation (collection and organizing the annotation), use machine learning approaches for irony detection, and testing for experimental and
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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a focus in economics, or related disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation
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the testing of newly devel-oped materials and the use of machine learning methods to process complex data sets. The focus is on techniques such as ultrasound, radar, computed tomography, acoustic emission
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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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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Dresden, Sachsen | Germany | 13 days ago
for the safety assessment of potential nuclear waste repositories, a deeper understanding of the mobility of Tc in the environment is required, in particular regarding the formation of stable Tc complexes in
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Carl von Ossietzky Universität Oldenburg | Oldenburg Oldenburg, Niedersachsen | Germany | 4 days ago
at the University of Oldenburg and involving national and international partner institutions. As a diverse and international team of scientists from biology, physics, chemistry, computer sciences and social sciences