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sound statistical models and methodology for the data-driven analysis of complex and dynamic systems, with the goal of enabling predictive, prescriptive, and pre‑emptive analytics. We work closely with
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will develop new mathematical tools to analyse brain imaging data using persistent homology, a method from topological data analysis (TDA) that captures the shape and connectivity of complex data across
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sequencing technologies (such as nanopore sequencing) has enabled the discovery and analysis of complex regions of the genome for the first time. Novel long read sequencing approaches developed in the Ryan
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We are looking for a highly motivated PhD candidate interested in AI-based methods, including machine learning and language technologies, for the integration and analysis of clinical, advanced data
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the new generation of economists, social scientists, managers and professionals with specific competencies in the analysis, interpretation and management of the complexity of economic, firm, and social
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] (AI-assisted Simulations of Microstructure driven MEchanical properties from high Throughput and multiscale analysIS), in the framework of PEPR DIADEM[2] , which aims to develop an advanced
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spatial immune cell niches in cancer. Advances in high-throughput spatial omics technologies measuring various analytes now capture this complexity in remarkable detail, providing groundbreaking insights
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description PhD Position: Agro-Economic Analysis of Legume-Cereal Mixtures
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approach: Repeated qualitative interviews: Three rounds of interviews (T0, T1 at 6 months, T2 at 1 year) will be conducted to track the progression of the patient’s journey. The analysis will focus
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multi-data analytics (e.g., health and climate/environmental data) and could include a range of data science methods, such as utilising geographical information systems (GIS), statistical analysis