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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud
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-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA sequencing and spatial transcriptomics data from active clinical trials
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attracting highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security
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cybersecurity allowing thus to validate and receive feedback from on-the-field cybersecurity practitioners. As generative AI (GenAI) platforms and large language models (LLMs) are increasingly integrated
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investigating their mechanisms using relevant in vitro and in vivo cancer models. The candidate will be expected to: Determine the effects of the identified VFs using various in vitro and in vivo assays and
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understand, explain and advance society and environment we live in. Your role Conduct research in risk analysis and statistical modelling of complex actuarial data Plan quality research, project managing
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resistance. This work will integrate spatial transcriptomics, advanced co-culture organoid assays, and in vivo models to decode the mechanisms underlying CAF-driven CRC evolution. Access to single cell RNA
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, transactions, smart-contract events) from public blockchains into research-grade databases Developing statistical, graph, and/or machine learning models to study transaction networks, illicit transaction
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vivo cancer models. The candidate will be expected to: Determine the effects of the identified VFs using various in vitro and in vivo assays and investigate the underlying mechanisms Contribute
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highly qualified talent. We look for researchers from diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud