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to training at various European Institutions and collaborate with particular French (Anthogyr) and Swedish (University of Gothenburg) partners. A longer stay abroad is expected. Experience with statistical
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background in programming (Matlab, python, …) familiar with Multi-body dynamic tools good knowledge of statistics familiar with signal processing, operational modal analysis Personal characteristics Strong
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statistical inference, optimisation, microeconomics, scientific methods Elective courses in economics, finance, or optimisation Management Science Dissertation on a topic in logistics, operations management
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background in programming (Matlab, python, …) familiar with Multi-body dynamic tools good knowledge of statistics familiar with signal processing, operational modal analysis Personal characteristics Strong
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collaborate with particular French (Anthogyr) and Swedish (University of Gothenburg) partners. A longer stay abroad is expected. Experience with statistical methods is an advantage, but not necessary Capacity
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data analysis workflow from data import/cleaning to descriptive statistics and at least one inferential model. Code must be included and clearly commented. This is required to demonstrate advanced
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knowledge about natural resource management Knowledge of software R Strong skills and/or interest in mathematical and statistical modelling is a strength Ability to conduct field work in remote alpine areas
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to metocean statistics and development of software packages related to the generation of said statistics. This work amounts to 25% (one year) of the total project period and allows the PhD project to run over a
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the interface between different scientific disciplines including ecology, evolutionary biology, mathematics and statistics, informatics, economics and social sciences. We aim to apply advanced statistical and
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statistics. Jon Terje Hellren Hansen via Unsplash Jon Terje Hellren Hansen We offer Involvement in an interesting research project Good career opportunities A good academic environment with dedicated