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challenges at the intersection of AI and cybersecurity, aiming to enhance model integrity, data privacy, and resilience to adversarial attacks. The research will explore methods to secure AI systems in real
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-building postgraduate conference with participation from across the pathway. Options for specialist training include GIS and spatial data analysis, advanced quantitative research in SPSS, transport modelling
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the pharmacometric research group, ensuring the successful delivery of its projects and research outputs. This includes developing PK/PD models using both clinical and pre-clinical data, supporting clinical trial
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Mouse Models Mara Sherman, PhD – Tumor Microenvironment in Pancreas Cancer Viviane Tabar, MD – Brain Tumors, Pluripotent Stem Cell Cancer Models Tuomas Tammela, MD, PhD – Evolution of intra-tumoral
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opportunities suited to green competitive advantage of key countries in Latin America, especially Mexico. The Sr. Research Data Analyst will build complex data models and conduct complex data analysis in support
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hold a PhD or MSc in Systems Biology, Biostatistics, Physics, Mathematics or a related subject. Experience with mathematical modelling of biological systems and the ability to effectively use statistical
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on the SAFT-g Mie equation of state. These models are applied to predict the behaviour of complex mixtures, with particular relevance to pharmaceutical systems. This position is part of the Mediforge
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to green competitive advantage of key countries in Latin America, especially Mexico. The Sr. Research Data Analyst will build complex data models and conduct complex data analysis in support of research
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will be responsible for: Liaising with other ECORES-WIND project partners, both in academia and the industry, and to enable quick and efficient sharing of information and modelling results within
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modelling. Furthermore, better knowledge of these properties helps refining the interpretation of data obtained from both active and passive remote sensing. PhD Topic This PhD project aims to quantitatively