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(PID) in high-voltage PV modules, and the challenges of spatial and temporal irradiance variability on large PV plants. Our team is dedicated to pioneering solutions that enhance the efficiency
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including transcriptomics, ATAC-seq, multi-omics and spatial transcriptomics, and also develop computational approaches for large-scale analysis of next-generation sequencing data. Our science and team is
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DTU Bioengineering and the CeMiSt Center are looking for a talented researcher for a position as Assistant Professor in Microbial Metabolomics and Big Data analysis. At the Center and the Section
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following qualifications: A strong background in meteorology, geophysics or similar. Experience with analysis of spatial data sets from satellites, ground based remote sensing, or weather models. Excellent