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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | about 2 months ago
Nature), for high-content CRISPR screening (Bock 2022 Nature Reviews), and CAR T cell engineering (Datlinger 2025 Nature); Condensates, Chromatin and Translational Control in Pediatric Cancer (Grebien Lab
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management, workflow management, High Performance Computing (HPC), machine learning and Artificial Intelligence to enhance our capabilities in making AI-ready scientific data. As a postdoctoral fellow at ORNL
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of Biological and Environmental Engineering at Cornell University is seeking a highly motivated Postdoctoral Associate to lead, develop and support innovative research at the intersection of microbial
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& Environmental Science offers a variety of undergraduate and graduate programs to educate, inspire and prepare the next generation of scientists. https://www.unr.edu/cabnr & https://www.unr.edu/bmb Search
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infrastructures organized in infrastructure platforms, of which the Vibrational Spectroscopy Core Facility (ViSp) is a central infrastructure for this project (https://www.umu.se/en/research/infrastructure/visp
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(iii) complex architectures with tightly coupled components hinder modular adaptation. To address these limitations, we research a physics-guided machine learning framework that integrates physical
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inverters to enhance grid flexibility, reliability and stability. • Apply machine learning and AI tools for the battery system health estimation and maintenance prediction and integrate analytics
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30 Jan 2026 Job Information Organisation/Company Umeå universitet stipendiemodul Department Faculty of Science and Technology, Department of Chemistry, Department of Chemistry Research Field
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of Biological and Environmental Engineering at Cornell University is looking for postdoctoral associate to support, lead and invent projects at the intersection of sustainable energy, synthetic biology, physics
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning