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lit. b (postdoc) Limited until: 31.12.2029 Reference no.: 4269 Among the many good reasons to want to research and teach at the University of Vienna, there is one in particular, which has convinced
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. M.Sc. in Business or Adjacent disciplines such as economics, psychology, engineering or computer sciences: e.g. M.Sc. in economics, M.Sc. in industrial engineering, M.Sc. in information management, M.Sc
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engineering or physics of electronic or optoelectronic devices is required Prior experience in numerical simulations, applied mathematics and/or machine learning is an advantage Interest and enthusiasm in
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completed doctoral degree (PhD) in data science, computer science, statistics, mathematics, natural sciences or related disciplines in-depth knowledge of data mining, data science, machine learning
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cloud data using state-of-the-art techniques (e.g., image processing, machine learning) A significant fraction of the work will be focused on the maintenance and strategic development of the group's
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, particularly with multiple objectives and/or at the intersection of machine learning and operations research Publications in leading, peer-reviewed journals in the fields of operations research, transportation
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intersection of Mathematical Finance, Stochastic Analysis and Machine Learning. The research areas cover a wide range of challenging topics such as (infinte dimensional) stochastic analysis, affine and
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) and clouds You will develop novel methods and analysis tools for in-situ aerosol and cloud data using state-of-the-art techniques (e.g., image processing, machine learning) A significant fraction of the
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Sciences, who develop, manage, and refine machine learning techniques for identifying copyists; Participation in the dissemination of research results through presentations and publications; Data management
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cloud data using state-of-the-art techniques (e.g., image processing, machine learning) A significant fraction of the work will be focused on the maintenance and strategic development of the group's