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gliomas. The project integrates generative AI, interpretable models, uncertainty estimation, and federated learning to improve clinical decision-making, data privacy, and personalized medicine
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of construction sites and information management Mathematical models for infrastructure impact and infrastructure economics Eligibility: PhD obtained between 1 January 2019 and 31 December 2024 (date of thesis
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. Participation in the cannulation and extraction of porcine organs from animal models, following established research protocols. Support in training in the extraction and cannulation of porcine kidneys and livers
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, using neuroimaging, multi-omics, and AI to advance precision psychiatry. Our work centres on computational models linking environment, brain systems, and behaviour, with a focus on risk, resilience, and
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device-level properties of amorphous graphene nanoribbons and related structures. This will provide a bridge between atomistic material modelling and experimentally measurable device characteristics
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distribution, and therapeutic efficacy in joint disease models. Technology Translation: Drive the translation of the nanomotor platform from preclinical research toward clinical application. Data Analysis
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, or Applied Mathematics •Strong experience in statistical programming using R. •Experience analyzing clinical, epidemiological or public health data. •Knowledge of regression modelling, longitudinal data
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cell culture models. Experience with in vivo imaging. Competencies and Skills: We value not only technical expertise but also the demonstration of core competencies such as Communication, Teamwork and
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vitro biofilm models of clinically relevant, antibiotic-resistant bacteria. Quantify the bactericidal activity of a library of PSC compositions against planktonic and biofilm-grown bacteria, using time
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models). Expert use of a chemical synthesis laboratory, a wide range of physicochemical and material characterisation is required. Moreover, in vitro and in vivo expertise, will be essential to determine