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Field
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learning methods and applied AI tools, including experience with large language models (LLMs) - spanning open-source models, LLM architecture, prompt design, and agentic AI frameworks - to help
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document a strong quantitative background and interest in one or several remote sensing and data science approaches. Must document scientific programming skills, specifically for data processing and
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skills on Data Analytics and Machine Learning, in particular on distributed ML. Must have very good programming competence in Python, Java, C/C++ or equivalent Fluent oral and written communication
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. The Master’s degree must include a thesis of at least 30 ECTS. Programming skills in Python, R or equivalent scientific computing languages. Experience in bioinformatic analysis of genomic data
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modeling and database or data systems engineering. Prior research experience with large, heterogeneous databases and quantitative models. Documented capabilities in programming like Python, R, SQL, or
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documentation must be in English or a Scandinavian language. General information The best qualified candidates will be invited for interviews. Please see the guidelines and regulations for
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(including deep learning and/or reinforcement learning) numerical simulation of quantum dynamics Proven programming skills (e.g., Python/Julia/C++), including experience with scientific computing tools
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degree corresponds to the profile of the post. Documented knowledge of statistical theory and methods and core machine learning methods. Documented Python programming skills. Excellent skills in written
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, programming in R, Matlab or Python. Excellent skills in written and oral English. Personal suitability and motivation for the position. The doctoral dissertation must be submitted for evaluation by the
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programming environments, especially R or Python; the applicant’s ideas concerning how the OCCPOL data could be developed and used; and motivation to participate actively in a collaborative research project and