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frames). Project background The work focuses on data-driven generation of structural systems. You will be involved in developing, experimenting with, and evaluating machine learning models that help
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Research focus: Molecular genetics in Arabidopsis to dissect key signaling components linking immune perception to metabolic regulation Phosphoproteomics and targeted metabolite analysis to identify
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COMPAS XR framework developed at ETH Zürich. Project background The successful candidate will work at the intersection of computational design, XR, human-computer interaction, and robotic fabrication, with
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Ph.D. Position in Organic Chemistry, Polymer Chemistry, and/or Sol–Gel Chemistry & Materials Science
that link molecular design to macroscopic performance in porous polymer aerogels The project is fundamental in nature but is embedded in an industry-sponsored framework that provides clear relevance
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data (what type and where; and what your role was) Diplomas Copy of your MSc thesis (or term paper if the thesis is not yet submitted) Summary of your MSc thesis (max. 1 page) 2 scientific references
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application with the following documents: A link to an online portfolio (e.g. GitHub, GitLab, etc.) of previous work that shows the programming code for a data projects (if no public portfolio exists, you can
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environments (Schmidt, Science, 2022) — especially in the context of drug–host microbiome interactions — and developing dedicated tools and analytic workflows for the novel data modalities generated by Record
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. As part of your role, you will: Take technical ownership of spacecraft avionics subsystems, acting as the primary technical authority for onboard computing and data handling within the assigned project