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of collaborators in ecology, envi-ronmental genomics, pollinator biology and biodiversity monitoring. Key Responsibilities The post doc will: Design and coordinate large-scale field studies across multiple seasons
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intelligence, starting 1 April 2027. You will design new sequence-to-expression deep learning models that predict gene expression from DNA sequence in plants, using new experimental datasets generated in
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microfluidics with semi-permeable capsules, fluorescence-activated cell sorting, and long-read sequencing, into analytical workflows tailored to protists in diverse environmental samples. Improving single-cell
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laboratories located in the Mærsk tower with access to state-of-the-art facilities for cell engineering, next-generation sequencing, flow cytometry, and mass spectrometry. Scientific environment CGR is located
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. Experience with one or more of the following will be considered an advantage: RNA sequencing or other omics technologies, including data analysis; advanced microscopy or image analysis; renal physiology
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take approaches combining mouse developmental genetics, cell-type-specific viral tracing, ex vivo electrophysiology, opto/chemogenetics, in vivo imaging, single-nucleus RNA sequencing (snRNA-seq), and
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science. The position will include collaboration within the Center, aligning with strategic initiatives across the partner institutions, involving seven departments at the University of Copenhagen and
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including bio-informatic processing To have experience with nucleic acid molecular manipulation incl PCR and experience in next generation sequencing -primarily on the illumina platform. To be eager to learn
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for model development, both quantitative data and sequencing data, covering Denmark and selected European countries Place of work and area of employment The place of work will be at Aarhus University
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for downstream sequencing and imaging. Performing MALDI mass spectrometry and spatial transcriptomics to characterize biological niches within mouse and human tissue samples. Performing quantitative imaging