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themes at Cranfield University. The manufacturing capability is world leading and combines a multi-disciplinary approach that integrates design, technology and management expertise. We link fundamental
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proficiency in the lab's core research platforms (e.g. PCLS, in vitro and in vivo cell based assays, animal surgical models). - Contribute substantively to the preparation of extramural grant proposals
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expertise and funding in human and model organism research including Drososophila melanogaster and microbes; as well as ‘omics - genomics, transcriptomics and metabolomics. They utilise a multi
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Leibniz-Institut für Astrophysik Potsdam (AIP) | 2 months ago
modelling. At the core of this newly funded Leibniz ScienceCampus SCALES are next-generation simulation techniques, hybrid modelling strategies, and the use of machine learning, particularly neural networks
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Systems biology emphasises a multi-level, integrative approach to understanding how living organisms work. With our close links to the polyomics facility, we apply a full range of post-genomic
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history experiences, and honors/awards Description of your goals, related experience, and related skills – refer to NETL's Core Competencies and ongoing projects when applicable Transcripts – Click here for
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development of safe, effective, and consistent EV-based therapies. In this project hands-on analytical wet-lab experiments, including cell biological analyses, multi-omics mass spectrometry and nanoparticle
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understanding of the mechanisms that govern debris flow motion is a core research topic in the Chair of Engineering Geology at ETHZ As part of this, the group collects and analyses an unprecendented
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Conversational Simulation This project addresses these challenges with two core components. The first is a simulation environment that turns self-report tools such as PHQ-9 into synthetic, multi-turn
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specifically interested in: Data-centric AI: Advancing machine unlearning, privacy-preserving techniques, and robust data curation. AI Safety : Ensuring robust alignment and safety in multi-agent LLM