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knowledge in the field of machine learning, in particular deep neural networks Practical experience in the application of machine learning algorithms for both regression and classification problems Excellent
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on best practices and current developments in areas such as research software engineering, research data management, machine learning in the Leibniz Association, as well as at national and
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expertise in computational materials science, density functional theory, machine learning, etc. Ability to work within an interdisciplinary team of scientists, engineers, and students. Excellent knowledge
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Data, geodata) Data visualization, georeferencing and web mapping (e.g. D3.js, open source GIS, R, Shiny)Programming, testing and documentation (e.g. Python, R, Jupyter, git) Machine learning and
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, these information systems address the needs and interests of the various target groups. Data assimilation and aggregation is done using machine learning and modeling. Within the project, we are looking for a Student
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spatial database management, in data governance and the establishment of user and linked data services. Competencies in the fields of data literacy, spatial data science, GeoAI, machine learning and
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spatial database management, in data governance and the establishment of user and linked data services. Competencies in the fields of data literacy, spatial data science, GeoAI, machine learning and
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results Motivation to learn and communicate about Planetary Boundary Science Analytical interest in and understanding of political and scientific debates Project management skills and experience in
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possible. She/he will contribute to ifo’s main research topics with his/her independent research applying a combination of state-of-the-art machine learning and causal inference methods to innovative and