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GIScience, geoinformatics, spatial data science, spatial analytics, or a related field; experience with diverse spatial analytical methods; strong programming skills (e.g., Python) and version control
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, urban analytics, geoinformatics, or a related field; experience with foundational AI model development/fine-tuning and machine learning and/or deep learning; strong programming skills (e.g., Python
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engagement and participatory research with quantitative system modelling of our research group; experience with systems modeling and computer programming (e.g. Python); strong communication and scientific
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assessment. Programming and data-analysis skills in a reproducible scientific workflow, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work
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). Experience in multi-modal data integration for prioritizing disease-specific targets: combining quantitative multi-omics approaches (es. RNA-seq, Ribo-seq, proteomics, immunopeptidomics). Strong programming
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transformers, self-supervised learning, foundation models, autoencoders or related architectures; • strong programming skills in Python and experience with a deep-learning framework such as PyTorch