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Field
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-Talisman Lab, please click here . As a successful candidate, you will: Purify EVs from cultured cells and plasma using different analytical platforms. Perform imaging experiments using super-resolution
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learning algorithms to support research in IDMxS. Key Responsibilites: Apply/ improve/ develop machine learning algorithms to process (e.g., classify, predict) data/ images collected by IDMxS. Help supervise
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studies how cancer and healthy cells respond to irradiation and DNA‑damaging drugs, using quantitative live‑cell imaging at the single‑cell level. We welcome applications from recent PhD graduates
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systems using computer vision, quantitative image analysis, deep learning methods for detection, diagnosis, and quantitative analysis of abnormalities with multimodal data, including clinical and
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imaging at the single‑cell level. We welcome applications from recent PhD graduates interested in these or related areas, especially those with expertise in quantitative in-vivo and ex-vivo imaging
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tissue imaging, spatial multi-omics, and AI-driven analytics. The successful candidate will lead projects aimed at dissecting the molecular and cellular mechanisms that govern tumor progression
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of cryptographic algorithms through solving polynomial systems of equations. It is crucial for building confidence in quantum safe cryptography, as well as novel symmetric encryption algorithms designed for use with
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, should you wish to send your application in a digitally encrypted form.
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quantum safe cryptography, as well as novel symmetric encryption algorithms designed for use with advanced protocols, such as fully homomorphic encryption, multi-party computation or zero-knowledge
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to experimental campaigns and will use image-derived structures (including XCT images where available) to develop mechanistic, validated mathematical multiscale models. We are recruiting a Postdoctoral Research