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, provided that they use the time allotted to continual professional development to complete the required courses within two years of employment, or that they apply for validation of prior learning. For other
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quantified, and machine learning will be used. Duties As a PhD student, you will work toward a doctoral degree as the final goal, according to the goals specified in the Higher Education Ordinance. In parallel
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based on advanced methods in statistical modelling, machine learning (including artificial neural networks) and geographic information analysis. You will be part of two dynamic research environments
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. Your tasks will include conducting independent research in the subject area at
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for version control. Ability to quickly learn new skills. High proficiency in Unix/Linux environments. Excellent verbal and written English skills. Additional qualifications In addition to the qualification
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development to complete the required courses within two years of employment, or that they apply for validation of prior learning. For other qualification requirements, please refer to Karlstad University’s
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collection (experiments, surveys). Expertise in advanced machine learning techniques and large language models (LLMs) —including web scraping, text mining, and neural networks—is considered a strong merit
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-dimensional statistics, discrete random structures, insurance mathematics, stochastic control theory and statistical machine learning. Subject: Mathematical Statistics Subject description: Mathematical
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The Department of Ecology, Environment and Plant Sciences invites applications for postdoktoral fellow for the project “Harnessing evolutionary transitions, machine learning, and genomics to decode pollen