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the perspective towards generating data for entrepreneurial seed funding (GO-Bio etc.) for a further development of the technology towards the market. In that sense we also highly encourage candidates that would be
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computational biology, bioinformatics, systems biology, bioengineering, chemical engineering, or a related discipline Knowledge and experience in the analysis of metagenomics and/or biological high-throughput
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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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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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) and the German Academic Exchange Service (DAAD) since 2007. Under this CAS-DAAD joint programme up and coming young Chinese scientists from the University of Chinese Academy of Sciences (UCAS) and CAS
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corpora data correlation. Requirements: A master’s degree in Computational Linguistics, Computer Science or related fields. Solid background in Machine Learning and Natural Language Processing Experience
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of Engineering and Design. Our teaching and research focus lies on computer-based development of engineering products, particularly on the planning and realization of built facilities using computational modeling
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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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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 7 days ago
Assistant position, with the successful candidate embarking on a PhD programme at LSHTM. It is anticipated that the role will lead to a further 18 month funded opportunity at Max Planck Institute
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, environmental or natural resource economics) or related disciplines strong analytical (i.e. microeconomics, production or resource economics) and methodological skills with a focus on quantitative data analysis