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Field
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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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requested not to be included on the list of applicants. If you disclose that you have an immigrant background, disability, or gaps in your CV, this information, in anonymized form, may be used for statistical
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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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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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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
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to psychological and clinical measures and outcomes, epidemiology, statistics, and bioinformatics. Work in an environment of scientific excellence and interdisciplinary collaboration IMPRS-TP is a joint initiative
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Master in Experimental Psychology, HCI, UX or related fields Experience with research methods in social sciences (e.g., empirical research, experiment design) Experience in statistical methods is
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for empirical statistical analysis, as well as possible experimental designs to validate findings. Empirical setting The research will utilize data from the Danish Innovation Fund, integrated with databases
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-average university degree in psychology, human factors, or a related field good knowledge of methods and statistics, especially quantitative approaches strong interest in research good English skills
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., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis, machine learning, deep learning