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experience in forest inventory metrics, and statistical analysis, including predictive modeling techniques. Ability to conduct fieldwork in forested environments, including operating handheld equipment
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Enthusiasm for conducting high quality and innovative empirical research in Finance Intellectual curiosity and an interest in pursuing a career in academia Strong statistical training and quantitative
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Science, and their responsible applications. Ideal candidates will have: An M.Sc. degree (or equivalent) in Computer Science, Statistics, Mathematics, or related fields. Strong programming skills in Python
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forestry, environmental science, ecology, or a related field Strong analytical skills, with experience in forest inventory metrics, carbon estimation methodologies, and statistical analysis, including
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of AI. The ideal candidates will have a background in computer science, statistics, mathematics, or related fields, as well as an interest in social science research methods and theories. The PhD
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or microfluidics and ideally in quantitative data analysis. As a theoretical candidate, you have knowledge in quantitative biology, soft matter/complex systems physics or statistical physics. You enjoy working in
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mathematics, (theoretical) computer science, machine learning foundations, electrical engineering, information theory, cryptography, statistics or a related field. - Advanced knowledge of probability theory