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with instructors and students to analysing multimodal learning data (e.g., individual as well as collaborative verbal interactions, student gestures, task and activity sequences) and evaluating long
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which you will be automatically redirected to an external site after 5 seconds) Save job Click to add the job to your shortlist Send job Job Details Are you interested in using machine learning to
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programming skills in Python and/or R. Experience with data curation, large-scale datasets, and genetic and machine learning methods. Interpersonal skills and collaborative competency Qualification
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, the project may include network analysis, geospatial analysis, scenario modelling, uncertainty analysis, machine learning and other AI-supported approaches. The candidate will build on selected
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will combine computational method development with experimental spatial metabolomics including signal preprocessing, machine learning, spatial statistics, image registration and interactive software
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regular shorter stays in Aarhus and online collaboration. Experience with one or more of the following will be considered an advantage: active-learning strategies for force-field construction, Green
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Postdoc in first-principles modelling and machine-learned force fields for correlated disorder in...
more of the following will be considered an advantage: active-learning strategies for force-field construction, Green-Kubo or Boltzmann-transport methods, defect thermodynamics, and simulation
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or a related field, with an interest in AI, machine learning, and NLP. • Experience or education in health data science or a health-related field is a plus. • Strong programming skills in Python
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disciplinary boundaries and are able to connect molecular data with ecological and environmental information. You should be able to work independently while also contributing actively to a collaborative