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, or a related discipline Interested in climatology/meteorology as well as quantitative methods Prior experience in programming is a plus (e.g., using R or Python) Good communication skills and a high
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and networking opportunities within the Munich AI ecosystem and within structured graduate programs: the Munich Centre for Machine Learning (MCML), the Munich Data Science Institute (MDSI), the local
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, Machine Learning, or a related field. Excellent programming skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow). A solid understanding of recommender systems, deep learning, and
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knowledge of quantitative methods, particularly in statistics and econometrics; experience in machine learning is a plus Background in business/management/behavioral science Experience with programming
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in production engineering issues and their investigation Enjoyment of supervising and programming technical systems Purposefulness and independent working style Creativity and willingness to experiment
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Mathematics (analysis, numerics, modeling) or in a comparable program with a strong mathematical focus and knowledge in, for example, functional analysis as well as the theory and numerics of PDEs. Strong
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related field PostDoc track: PhD in a relevant discipline with a record in medical image analysis / ML Strong programming skills (e.g., Python, PyTorch/TensorFlow; image processing frameworks) Background in
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: Completed master studies in the field of environmental sciences, forestry, landscape ecology, remote sensing or related fields Interested in remote sensing, quantitative methods and programming Prior
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engineering, or geodesy with a specialization in Deep Learning, or in a comparable thematically appropriate discipline. In-depth skills in programming and working with Deep Learning methods. Expertise in
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cooperations efficient and productive. As Research Associate you will also support our teaching activities in several Bachelor and Master programs offered by the School of Engineering and Design and the School