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Field
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association study (GWAS) and transcriptome wide association study (TWAS), is taken in the SwAsp collection to identify genetic variation in NUE and candidate genes that are functionally validated in transgenic
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associated with the position will include both wet-lab and dry-lab methodologies, as well as clinical studies. The project will focus on cancers including, but not limited to, pancreatic ductal adenocarcinoma
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bioinformatics including NGS (Nanopore, Illumina, PacBio) Experience with automation and coding in Python or other programing languages Experience with protein software tools like AlphaFold3, Boltz2, PyMOL
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sequencing, advanced microscopy, CRISPR-based genome editing, and bioinformatics. The lab uses diverse cell models, including embryonic stem cells and their differentiated derivatives. The research in
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Bioinformatic analysis of single cell transcriptomic data Key criteria for the assessment of the applicants The following requirements for the candidate will be assessed as key criteria for the recruitment
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on the department can be found at: https://icmm.ku.dk/english/ Project description The work will be focused on elucidating the mechanisms of RNAPII associated factors and how these impact transcription dynamics