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You will collaborate closely with RCA staff, PhD students, and external partners, contributing to cutting-edge, design-led robotics innovation. Outputs are expected to be published in high-impact
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Automation group will develop novel machine-learning based control algorithms that allow for real-time adjustment of OSA therapy. The main challenge is to develop robust machine learning algorithm which can
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-matter BEC in a telecom range Phys. Rev. B 110, 134321 (2024) Your role and goals The successful candidate is expected to lead the experimental effort with a team of PhD and master’s students and
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will focus on the prediction of genetic interaction networks and image analysis for automated phenotyping. We welcome interest in developing both ongoing and novel research projects in the lab, and are
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to develop automated segmentation tools and diagnostic aids for otologic conditions. Working with ENT surgeons, audiologists, and AI researchers, you'll have access to datasets including audiograms and
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-economic environment in Morocco and Africa. HTMR provides highly automated and parallel approaches to the development of new materials and processes. HTMR allows scientists from all UM6P research community
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for solids, liquids, and gases, isotopic analyses, automated throughput analyses, and the production of reference material standards. Major Duties/Responsibilities: Develop front-end introduction systems
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for the following full-time postdoc position to begin as soon as possible. Postdoctoral position in automizing organoid manufacturing (f/m/d) The position is funded by the Carl-Zeiss-Stiftung (CZS) Background: We aim
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The successful candidates should have the following qualifications: A PhD in Environmental Toxicology, Chemical Engineering, Environmental Chemistry, Materials Science, or closely related fields. Solid
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methods (e.g., PCA, PLS-DA, clustering, neural networks) to enable automated, polymer-specific classification. Optimize workflows for high-throughput imaging and real-world sample variability, minimizing