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Field
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18 Months Fixed Term, Whole-time Post Please note that the successful candidate can be hired either as a Post-Doctoral Researcher or a Research Assistant, based on their qualifications and level of
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: A doctorate in a Machine-Learning related field A deep knowledge of Control Theory, both classical and deep learning based A solid publication record in top level ML venues such as NeurIPs, ICML, and
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cellular mechanisms underlying cancer immunoediting in skin cancer. Current research focuses on understanding the role of natural killer (NK) cells in shaping tumor evolution and controlling cutaneous
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and AI-based approaches, including predictive modeling, stratification, explainable AI, and integrative multimodal analysis. The scholar will have opportunities to lead first-author publications
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controlling the entire image chain, from modeling the acquisition system to specific knowledge of the application domains. Another common point of much of the research carried out by the team is the use
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, cardiac CT, ECG, portable ultrasound, and multimodal clinical data. Building scalable pipelines for image ingestion, DICOM/PACS interoperability, preprocessing, annotation, quality control, model training
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regulatory decision-making around the implementation of these technologies. A key component of the work will involve developing an ex-ante economic model to identify cost-effective strategies for implementing
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planning. The project combines agent-based modelling, large-scale mobility data, transport networks, generative modelling, resilience indicators, and equity analysis. A central goal of this recruitment is to
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-supported educational tools, including large language model-based agents, with attention to instructional quality, learner interaction, and responsible use. Experience using Arduino microcontrollers
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and a passion for investigating the role of the tumor microenvironment, in particular CAF-driven epithelial plasticity, using advanced experimental models. The primary research focus will be to define