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to join our dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of
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research funding • Strong organizational and management skills, with the ability to manage multiple tasks in parallel • Excellent analytical skills and ability to present interdisciplinary research
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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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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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: 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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, 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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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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listed as the strongest German business school for research, and #9 in Europe for M.Sc. programs in entrepreneurship. The TUM Campus Heilbronn is a dynamic organization whose goal is to achieve excellence
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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