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Field
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and regions involved in protein interactions. In recent years, the field has moved from the analysis of purified complexes to proteome-wide studies thanks to fundamental instrumental and bioinformatic
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analysis of complex biomedical datasets. The research environment is highly interdisciplinary, bringing together expertise from machine learning, statistics, data science, and healthcare research
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on complex problems involving the development of new theories and methodologies. The research will be largely focused on the development of predictive computational tools for the analysis of the spatial spread
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synchrotron X-ray scattering data, including X-ray diffraction and total scattering measurements. The research will emphasize extracting physically meaningful descriptors from complex scattering datasets and
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analysis using software such as SPSS, R, Stata, or equivalent. Strong written and verbal communication skills, including the ability to translate complex research findings for non-specialist audiences
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Your Tasks Lead analysis of single-cell and pertubation datasets across glioma patien derived models and tumor tissue Integrative analysis of multiomics and pertubation datasets Drive projects
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mathematical, statistical, and machine-learning-based analysis of complex data sets, such as hypothesis testing, supervised/unsupervised learning, linear models, etc. Experience with atlas-scale single-cell data
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Is the Job related to staff position within a Research Infrastructure? No Offer Description Gammapy is an open Python library for astrophysical very-high-energy (VHE) gamma-ray data analysis. Amongst
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; experience performing metabolic analysis using mass spectrometry, especially in complex matrices; experience with metabolomic pathway bioinformatics analysis and development of rapid point-of-use analytical
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develop expertise in high-resolution cryo-EM, cryo-ET, and the reconstitution of membrane-associated signaling complexes. Data Analysis: Use computational tools (e.g., CryoSPARC, ChimeraX) to analyze and