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of Universidad Politécnica de Madrid working in the SafeNet project funded by Horizon Europe (https://safenet-project.eu/ ) and will contribute to the following main tasks and analyses, as well as to other general
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learning frameworks such as PyTorch or TensorFlow is an advantage); Affinity with probabilistic modelling and spatial data analysis; Interest in the physical behaviour of water systems and hydrology (prior
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/industry research and play an important role in impacting patients’ lives. For more details, please view https://dr.ntu.edu.sg/entities/person/Lynn-Yap The selected candidate will perform a variety of
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direct therapies that will prevent liver cancer progression and disease. The post holder will be expected to contribute to the design and implementation of experiments along with the subsequent analysis
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-CT experiments as part of the user program but the methodology has not been optimised. In this project, we will optimise the scanning method, the hardware and the analysis software to make
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cardiovascular disease (CVD) in Type 1 (T1D) and Type 2 (T2D) diabetes and obesity. This position is engaged in the field of Spatial transcriptomics and bioinformatics. This position supports the analysis
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, or similar technologies. Familiarity with GIS platforms for spatial analysis of energy infrastructure and load data is also essential. The candidate is able to manage complex data systems while maintaining
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mice and humans. The successful candidate will have substantial experience and skills in single-cell/nucleus RNA sequencing analysis. Additional projects will include analysis of spatial omics data
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genetics, genome engineering, advanced microscopy, quantitative image analysis, single-cell and spatial multi-omics, biomaterials, and engineered in vitro model systems to investigate how the aging
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researcher will contribute to the development of a novel time-resolved fluorescence lifetime measurement approach, in close connection with methods based on single-molecule brightness analysis. The objective