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Field
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module I: Basics in quantitative and qualitative methods Compulsory module II: Statistics and econometrics or Advanced methods in qualitative research Compulsory module III: The sociological and economic
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animals, while Prof Durbin's works on computational genomics and large scale genome science, including the development of new algorithms and statistical methods to study genome evolution. Moving forward
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qualifications Masters degree in a relavent scientific field, such as biology, ecology, or natural resource management Experience conducting field work Basic statistical competence The following experiences and
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quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with a strong team orientation excellent spoken and written English and the
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excellent communication skills and will to collaborate with researchers from different disciplines. You have proficiency in data analysis and statistical software packages. You have problem solving skills
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papers This is part of your personality: MSc in Physics, Chemistry or related areas at the time of recruitment (any time between June and September 2025). Preferred background in statistical physics, soft
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understanding of principles of hydrometallurgy and minerals processing. - Strong skills in collecting, recording, and analysing experimental data and the statistical analysis of data. - Ability to interpret
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and probabilistic programming. This exciting new field of research combines knowledge from the machine learning, programming languages, scientific computing, and statistical physics communities
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problems Proficiency in data analysis and programming using at least one statistical program such as R, Python, or similar programming languages Experience with GAMS, GTAP, and Exiobase is an asset. Skills
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the organising principles of biological information processing, focusing on the underlying physics of computations and sensory environments. This exploration has led to developing models and advanced statistical