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Field
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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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software as python packages Report findings and methods in conference and journal papers Your profile Masters, Diploma or equivalent degree in IT/computer science/statistics/applied mathematics/data science
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 1 month ago
Bayesian statistics, AI-assisted inverse problems, planetary remote sensing, and environmental monitoring. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09787 Requirements Skills
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economics or a related discipline from a reputable university Strong knowledge in econometrics / applied mathematics / applied quantitative methods, with the ability to apply this knowledge to real-world
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Systems/Financial Mathematics/Probability, Applied Mathematics: Theoretical Physics, Pure Mathematics, and Statistics. The NMES Graduate School is home to the Faculty’s PhD students. It delivers a training
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planning, forest remote sensing, forest inventory and sampling, forest mathematical statistics and landscape studies. The department is also responsible for the implementation of the ongoing environmental
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on the number of top economics, finance, and mathematical statistics publications per professor over the last 5 years. It provides an international and stimulating environment with regular top research seminars
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broad range of areas, including causal inference and time-to-event analysis, clinical trials, epidemiology, high dimensional statistics, infectious disease, machine learning and mathematical modelling
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combining wave modelling, field observations, remote sensing, advanced mathematical methods and AI, the research will quantify spatial patterns of wave set-up, its statistical distributions and co-occurrence
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, mathematical logic or statistical learning theory. For PhD position 2, we appreciate prior experience in implementing deep learning models for graphs and networks. Our offer As a PhD candidate at UT, you will be