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well as to leading HPS and STS centers in Germany and around the world. The researcher taking on this position will be required to teach 5 hours per week, in accordance with postdoctoral workloads across Germany. The
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. Profound knowledge of at least one programming language, preferably Python. Previous experience in machine learning and deep learning. Practical experience with frameworks such as Keras or PyTorch Good
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data science, computer science, physics or a related field. Profound knowledge of at least one programming language, preferably Python. Previous experience in machine learning and deep learning
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weekly working time of 40 hours per week. The position can be filled on a part-time basis. Background: Addressing climate change and biodiversity loss requires a deep understanding of global land-use
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field such as computer science, bioinformatics, mathematics, computational life sciences, or related. Profound knowledge in machine learning, preferably deep learning for image data. Experience in
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environment (e.g. cleanroom, laboratory Deep knowledge of solid state physics and/or quantum information Experience with microfabrication and/or operating and calibrating quantum systems Experience with
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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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(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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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