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, develop methods to speed up this development by focusing on machine learning techniques to address sustainability challenges in chemistry research. We will explore novel pathways to process design and
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machine learning and deep learning, where you must be creative and motivated in searching and reading relevant literature, and developing novel models to tackle complex real-world problems in healthcare
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100%, Zurich, fixed-term The Swiss Seismological Service (SED ) at the Department of Earth Sciences at ETH Zürich invites applications for a fully funded 4-year PhD position in Machine Learning
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candidates should have Solid working knowledge of software tools and environments for application deployment, optimization, and performance analysis Background in modern machine learning models, such as
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for a closed-loop decision support system that can be verified in rehabilitation in many health conditions. This position is open for a postdoctoral researcher in the field of transparent machine learning
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mechanical experiments, control devices, acquire data and carry out post-processing operations. Other tasks comprise mechanical design (about 10%) and machining as well as electronics (about 10%). Examples
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scientist with strong skills in machine learning and hydro-meteorology. The main tasks of the successful candidate will be to translate the most recent developments in the fields of machine learning and Earth
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100%, fixed-term We are seeking a postdoc in biogeochemical modelling to work on the SNF-funded N2O-SSA project: Combining measurements, modelling and machine learning to improve N2O accounting
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novel methods at the intersection of advanced control, optimization, manufacturing science, and machine learning, to create the next generation of sustainable automation solutions for modern manufacturing
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at ETH Zurich. Our mission is to accelerate chemical discovery using digital tools. We predict chemical reactivity and molecular properties using the tools of machine learning, computational chemistry, and