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early metabolomic disruptions, followed by the genetic and biochemical dissection of the mechanisms underlying these alterations. The project takes advantage of recent transcriptomic and imaging data
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particular emphasis on integrating satellite LiDAR and UAV data with field observations. Applying statistical modelling, automated machine learning approaches, and artificial intelligence for the analysis and
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hold both the disease biology and data analysis in view at the same time. 3. Chemoproteomics of drug toxicity and efficacy You will use chemoproteomic approaches to characterize target engagement
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Demonstrated experience developing data-analysis pipelines, software tools, workflows or computational resources that are documented and usable by others Substantial experience in the analysis of high