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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 4 days ago
, Regional and Local Planning, or related fields; Experience working with Geographic Information Systems (GIS); Knowledge of databases and data systems; Experience in quantitative and spatial analysis methods
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and single-cell omics (transcriptomics, proteomics, epigenomics, metabolomics, meta-transcriptomics, etc.) data. Independently carry out computational and bioinformatics analysis for large-scale spatial
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, spatially resolved optical mapping, or multidimensional imaging and spectral analysis, is preferred. • Strong experimental, quantitative data-analysis, and problem-solving skills, with the ability
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datasets to identify regional spatial patterns and temporal trends in ecological processes and carbonate budgets across South and Southeast Asia. The ideal candidate will have strong research interests in
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with modern AI frameworks and APIs for developing agentic applications. Experience with multi-omics integration, gene regulatory networks, spatial transcriptomics, trajectory analysis, or chromatin
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/or geospatial analysis related to landscape dynamics in mountainous areas experience from or competence in processing and analysing remotely sensed or other spatially explicit environmental data; have
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. This 4-5-year project is supported by an NIH R56, the HNC SPORE, and other research funding. The postdoc will investigate the spatial and functional relationships between intratumoral bacteria and immune
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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 4 days ago
Europe Programme. The successful candidate will support research activities related to geographic information systems (GIS), territorial indicators, open science, public policy analysis, statistical data
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of the discipline or similar Main Duties The responsibilities may include some but not all of the responsibilities outlined below. Analysis of multiparameter CyTOF and flow cytometry data Analysis of spatial
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for: Analysis of bulk and single cell RNA-sequencing, spatial transcriptomics, and proteomics datasets Integration of experimental model data with public and clinical datasets Statistical modeling and survival