21 algorithm-development-"Helmholtz-Zentrum-Geesthacht" Postdoctoral positions in Switzerland
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-native plant species in mountain ecosystems based on a novel global dataset. In addition, the candidate is expected to join field campaigns in the Swiss Alps and will have the opportunity to develop
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. Empa is a research institution of the ETH Domain. The Laboratory of Advanced Materials Processing (LAMP) is a multidisciplinary research unit that develops innovative functional modification of materials
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Thun explores the possibility of high throughput materials development. In the context of our Materials Vision Tech initiative, we focus on multi-element gradient thin film systems, i.e. their rapid
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Swiss Federal Institute for Forest, Snow and Landscape Research WSL | Switzerland | about 12 hours ago
methods for image classification including machine learning and deep learning. You will develop clear workflows that allow for regular update of the derived models and maps. Furthermore, you will work
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opportunities to develop their skills in scientific communication through presentations at conferences and writing scientific papers as well as in management by co-supervising bachelor and master thesis
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. Empa is a research institution of the ETH Domain. The Urban Energy Systems Laboratory (UESL) pioneers strategies, solutions, and methods to support the development of sustainable, resilient, and
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immunoengineering. This position is part of our newly funded ERC Advanced Grant, which aims to develop genetically engineered feedback control circuits in human T cells to tackle challenging diseases. The successful
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, developing novel and innovative independent lines of research and significantly contributing to the lab's scientific vision.
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. Utilizing a combination of experimental and computational approaches, we develop and characterize novel functional materials and devices driven by robust nanoscale quantum effects. We are currently seeking a
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, particularly on measurements and searches using jet substructure and development of advanced techniques in particle tagging, including applications using machine learning, and are expected to take leading roles