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support predoctoral researchers in developing an original research and innovation project through international mobility. DETECTIVE (Data driven Excellence in Training of Epidemiological, Clinical
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of parameters such as molecular abundances, and interpretation using state-of-the-art radiative transfer and chemical models. The results of the work inform the development of future far-infrared space missions
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project will define cell-cell communication pathways and gene regulatory networks involved in normal and abnormal artery formation. Key findings will be validated in developing embryos and investigated
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editing (lentiviral transduction, Cas9 mRNA/protein electroporation) and supporting pooled CRISPR screens Managing primary human cell material, cell banks and laboratory inventories Supporting protocol
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on the laboratory’s expertise in conditionally active small molecules, we aim to develop antibacterial compounds that are selectively activated in response to infection. The interested candidate will focus on synthesis
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anticancer agents for the treatment of non-small cell lung cancer (NSCLC). Where to apply Website https://www.unimore.it/it Requirements Additional Information Eligibility criteria Eligible destination country
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the OEIS, pioneer the use of mobile phone apps at scale for patient reported symptoms, and align with blood sample collection, for use in future genomic analysis and personalised medicine. The post will work
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immunology, with the aim of developing improved cell-based immunotherapies for the treatment of cancer. Our research focuses on rationally harnessing and programming the immune system’s ability to perform
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Computer Science, Cybersecurity, Information Assurance and Security, Mobile Application Development, and Machine Learning. The Department also offers an M.S. in Computer Science and a Graduate Certificate in
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the consortium; the candidate's MSCA-DN mobility eligibility for the selected host country. The selected candidate will therefore be matched with the TUAI partner offering the best scientific and supervisory fit