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-scale assessment data, meta-analyses of meta-analyses) Methods and approaches to cumulative, living, and community-augmented meta-analyses Methods and approaches to include machine learning and artificial
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. Desirable: Proficiency in scientific programming (e.g. Python) and familiarity with data science and machine learning techniques. Experience with geochemical analytical techniques and working in a laboratory
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, and AI chatbot chats; (b) quantitative content analysis; (c)text mining and machine learning methods; (d) survey design and public opinion research; (e) election studies; (f) the Norwegian political
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will possess a relevant PhD or equivalent qualification/experience in a relevant field of study (e.g. data science, AI, machine learning, statistics, physics). They will be motivated to solve problems
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simulations using DFT (particularly of surface processes); kinetic Monte Carlo simulations; molecular dynamics simulations; classical and machine-learned force fields. Highly developed skills in scientific
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, sensor networks and measurement technology, grid computing and physics data analysis, machine learning, and interactive and collaborative systems. The prospective PhD candidate will be part of a research
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personal qualifications A PhD in data science, statistical genetics, quantitative genetics, bioinformatics, statistics, computer science, or closely related fields (required). Experience with large-scale
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training materials for research teams, focusing on data science and machine learning techniques in geoscience. Position description: PD [Research Fellow] [520112].pdf To learn more about this opportunity
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processing would be an advantage. Proficiency in statistical software (e.g., R, Python, SAS, or Stata). Experience with clinical informatics approaches (e.g., cluster analysis, machine learning, Bayesian
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the University's research culture and collaborative profile. Qualifications: PhD in Computer Science/AI or a closely related field. Extensive research experience in machine learning, deep learning, and self