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(n = ~1 million adults; 188,402 deaths observed), modeling spatial processes, and considering family risk factors. Duties of the postdoctoral associate include preparing area-level data, data analysis
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the fundamental factors governing cation mobility in aluminosilicate materials through an integrated experimental-theoretical-computational approach. The research will probe the spatial extent and timescales of ion
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NIMSB Technology Platform Leaders:Data Science, Single-Cell & Spatial Omics, Proteomics/Metabolomics
Single-cell and Spatial Omics: https://nimsb.unl.pt/wp-content/uploads/2026/03/SComicsTPL-1.pdf Proteomics/Metabolomics:https://nimsb.unl.pt/wp-content/uploads/2026/03/ProteomicsTPL-1-1.pdf Skills We seek
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. Process LiDAR data to support 3D analysis of terrain and settlements, integrating it with other spatial datasets to improve accuracy and create 3D models. Plan, execute, and process drone-based data
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statistical models. Within the Polarity, Division and Morphogenesis team, the candidate will work closely with biologists and physicists to develop approaches integrating spatial transcriptomics, cell dynamics
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captured from UAVs. The research will address the design of AI models capable of combining heterogeneous sensor modalities, including RGB, thermal, LiDAR, acoustic arrays, GPR, and X-ray backscatter
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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. The project will construct the first-ever Spatial Integrated Assessment Model of the global water cycle. Combined with global spatial data on economic activity, water usage, and atmospheric evaporation
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decision-support systems for sustainable forest-based supply chains in close collaboration with industrial partners. These projects aim to develop interactive methods, computational models, artificial
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models