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degree (PhD equivalent). Outstanding (top 10%) students holding a Bachelor's or Master's degree in economics or related fields (e.g., mathematics, statistics, business administration, accounting, and
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or population genetics/genomics and have a strong interest in studying genetic biodiversity. Previous experience with molecular lab work is a must; additional skills in bioinformatics and/or statistics
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Familiarity with statistics and programming experience in Python are advantageous Strong intention to be a part of international team with interdisciplinary questions We offer: An interesting and vibrant field
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outcomes Synthetic data generation (virtual patients) Statistical model checking to ensure statistical correctness of the results Machine learning–based classification and regression methods The candidate
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UiO within 3 months of start-up (or a binding agreement). Documented skills in advanced statistics, preferably using Stata and/or R. Excellent academic results and strong analytical abilities. Good
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computer science, bioinformatics, physics, engineering, computer science, statistics, mathematics) or in health science related fields (e.g. medicine, veterinary medicine, pharmacy, life sciences) is mandatory
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are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here. We hope you will apply
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these representations can be combined with concepts from physics‑inspired machine learning, drawing on statistical physics, dynamical systems, and stochastic processes, to design robust, interpretable, and mathematically
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classifications, infrastructures, and everyday encounters in and around official statistics and related data initiatives. The overall project combines historical/archival research, qualitative fieldwork (interviews
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skills in English Working knowledge of statistics. High level of motivation to work both as an independent researcher and as part of an international team capacity and willingness to provide assistance in