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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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Your position You will work on the development of a nanopore-based platform for single-molecule analysis of nanoclusters. Your research will include: • Establishing nanopore assays for detecting and characterizing individual nanoclusters • Engineering and purify protein nanopores with tailored...
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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20 Jun 2026 Job Information Organisation/Company ETH Zürich Research Field Chemistry » Computational chemistry Computer science » Other Engineering » Materials engineering Engineering » Other
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Atomically thin layers of various materials can be combined - almost at will - into novel artificial materials, with graphene structures being the most prominent examples. If two (or more) layers
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, including cutting edge quantum physics and chemistry, material science, nanotechnology, biochemistry, cell biology, or medical research. The SNI PhD programme includes multiple social events, trainings in
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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30 Jul 2026 Job Information Organisation/Company Empa Research Field Engineering » Materials engineering Engineering » Mechanical engineering Engineering » Other Researcher Profile First Stage
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Materials science and technology are our passion. With our cutting-edge research, Empa's around 1,100 employees make essential contributions to the well-being of society for a future worth living
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an interdisciplinary project in the field of biology, tissue engineering, material science, and chemistry. Complementary to experimental work, the candidate will work on computational models to understand and predict