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Field
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profile You are a proactive and analytically strong researcher with a passion for data science, mathematics, and financial markets. You thrive in multidisciplinary settings and enjoy balancing theoretical
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the areas of innovation management, the creation and growth of technology-intensive organisations, business analytics, and entrepreneurship. The research undertaken at the UCL School of Management has been
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, data analytics, and co-designed interventions. This is an exciting opportunity to contribute to applied research that informs urban policy and planning, particularly around air quality monitoring and
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science and energy technologies Basic knowledge of artificial intelligence and data analysis methods Programming skills, ideally in Python Independent and analytical way of working Reliable and thorough
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. The position is placed in the Division for Computer Networks and Systems and is formally employed by Chalmers University of Technology. Our research spans from theoretical computer science to applied systems
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is desired Expertise in the analysis of digital CT scan data is desired Familiarity with analytical tools such as R or Python for statistical and phylogenetic comparative analyses Experience with
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fields such as development or migration studies; demonstrated experience with qualitative and ethnographic research (evidenced in a Master's thesis); strong analytical and writing skills; familiarity, and
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, or interdisciplinary fields such as development or migration studies; demonstrated passion and experience with qualitative and ethnographic research (evidenced in Master's thesis); strong analytical and writing skills
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information: http://www.slu.se/en/departments/forest-ecology-management/ Read more about our benefits and what it is like to work at SLU at https://www.slu.se/en/about-slu/work-at-slu/ Name of research project
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, geometallurgy or related field Experience in either stochastics, deep learning or minerals processing is needed Structured and solution-oriented working style, analytical thinking and above-average committment