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motivated researchers with a MSc level knowledge in agricultural or hydrological sciences, with sound expertise in Remote sensing applications, big data integration, developing and applying deep learning
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models. Your tasks: Research, development, and evaluation of Machine Learning and Deep Learning methods Prototype development Literature review Publication and presentation of scientific results in
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and modeling * Experience with deep learning frameworks * Scientific software development * Excellent organizational skills and good mentoring capabilities * Fluent in English. Can communicate clearly
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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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focus on deep networks for solving inverse problems, learning robust models from few and noisy samples, and DNA data storage. The position is in the area of machine learning, with a focus on deep learning
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://www.cs.cit.tum.de/cmm/home/. Role Description As a Bioinformatician, you will play a crucial role in the development of new methods spanning deep learning sequence-based models, multi-omics and single-cell omics
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the 01.10.2022. Your Responsibilities: You will work at the cutting edge of privacy-preserving deep learning research with a focus on one or more of the following topics: - Optimal model design for differentially
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(ML4Earth). AI methods, and especially machine learning (ML) with deep neural networks have replaced traditional data analysis methods in recent years. The Technical University of Munich (TUM), together
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background in a technical field such as computer science, bioinformatics, mathematics, computational life sciences or related. Profound knowledge in machine learning, preferably deep learning for image data. A
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machine and deep learning Programming experience with Python and Pytorch Strong analytical and problem-solving skills Excellent communication & interdisciplinary skills Fluency in English (written and