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Postdoc in experimental studies of phase behavior of ABC-miktoarm star block copolymers in thin f...
experimental soft matter self-assembly studies We seek a highly motivated and self‑driven individual who is also a strong team player, thrives in an interdisciplinary environment, and demonstrates excellent
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of Science and Technology (LIST) is a Research and Technology Organization (RTO) active in the fields of materials, environment and IT. By transforming scientific knowledge into technologies, smart data and
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and international research environment where you get an opportunity to contribute to high-quality research at the highest international level. Your mission We are seeking a postdoctoral researcher to
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spoken and written English. Ability to work both independently and collaboratively in an interdisciplinary research environment. Particular emphasis will be placed on experience working at the interface
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for the environment, as the emissions associated with the entire life cycle of the packaging are much better than for disposable packaging. However, companies that use these reusable packaging do not have real-time
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within a multidisciplinary research environment Support mentoring junior researchers and contribute to project organization Independently planning experiments, analyzing data, and contributing
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advanced imaging, genomics, and metabolic profiling. A highly collaborative environment across FMI and Novartis, combining basic and translational research expertise. Opportunities for scientific development
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with advanced imaging techniques (e.g., cryo-EM, cryo-ET, or advanced fluorescence microscopy). You are able to work independently as well as in a collaborative, interdisciplinary environment. What we
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: Monday – Friday, 8 a.m. – 5 p.m. Summary Baylor College of Medicine is part of the world-renowned Texas Medical Center located in Houston, Texas, which offers a highly interactive environment and a strong
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interdisciplinary environment spanning explainable AI, causality, knowledge representation, and neural networks. Research (90%) research in probabilistic machine learning and neuro-symbolic AI (e.g. neural nets