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knowledge of IRT models, a basic understanding of common estimation methods, and strong programming skills in R, Python, or another relevant computing language. Experience with machine learning methods is a
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we are looking for (Selection Criteria): Essential: A PhD (or near completion) in geochemistry, geology, data science or a related discipline. Demonstrated knowledge of, or strong interest in critical
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available in the further tabs (e.g. “Application requirements”). Objective This scholarship programme allows scientists to carry out research with German colleagues at universities, universities of applied
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the Medical Research Council. The Research Fellow will be using Natural Language Processing (NLP) methods, with a special focus on generative Large Language Models (LLMs), to interrogate a very large sample of
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, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language
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requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up
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environment Career guidance throughout the postdoctoral program and together with you we will prepare a career plan, which containsthe skills and knowledge you will acquire Open and inclusive working
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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), MEng/MSc (Research Associate) in Electrical Engineering, Computer Science, Statistics, or other related fields. Solid Mathematical skills. Experience in one of the programming language – Python, Matlab
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design using computational methods Organic synthesis MD simulations Knowledge of a scripting language The candidate must demonstrate a structured approach to work, a strong commitment for hit discovery and