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Collaboration together with CERN and a number of other institutes worldwide and has over the years contributed to a number of space-specific physics models and other software capabilities and applications to
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-Independent Acquisition (DIA), Parallel Reaction Monitoring (PRM), Quantitative proteomics workflows, Data normalization and quality control strategies, Strong experience in processing and interpreting
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methodological and conceptual impact. The historical research is intended not simply as a parallel study, but as a source of conceptual insight for the contemporary physics and mathematics in the project. The
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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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Max Planck Institute for Psycholinguistics | Nijmegen, Provincie Gelderland | Netherlands | about 1 month ago
background, with experience in one or more programming languages (e.g. R, Python, Perl, or shell scripting) Desirable experience includes : Structural equation modelling (e.g. lavaan) Meta-analysis methods
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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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models) or probabilistic modelling is a strong plus. You have good programming skills in Python and experience with a deep learning framework such as PyTorch. You enjoy interdisciplinary work: you will