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Bioinformatician at the level of postdoc/assistant professor for the Center for Translational Neuromedicine

Overview of the research team



Center Translational Neuromedicine (CTN) at the Faculty of Health and Medical Sciences of the University of Copenhagen is seeking a highly trained and motivated bioinformatician to join its international and interdisciplinary team.



Conducting basic and clinical research, the center is comprised of two collaborating divisions with the combined aim of understanding the biology of human glia, specifically glial progenitor cells, oligodendrocytes, and astrocytes, and their involvement in neurodegenerative and psychiatric diseases including disorders of central myelin (multiple sclerosis and leukodystrophies), Huntington’s disease, schizophrenia, frontotemporal dementia, and glial tumors. Consult our website (http://ctn.ku.dk) for more information on research topics.



Work description



The center conducts extensive laboratory experiments generating vast amounts of data including but not limited to messenger, small, and micro RNA sequencing, quantitative proteomics, CHiP, ATAC, and methylation sequencing. For the studied diseases, the ultimate bioinformatics aim is the construction of glial regulatory pathways on multiple molecular levels and their dysregulation patterns under the disease condition. For a wide array of multi-omics datasets, the selected candidate will be performing computational analyses ranging from primary quality control of raw data to identification and prioritization of disease-dysregulated genes and pathways, as well as integration of data derived from these disparate datasets into coherent regulatory frameworks. As a resident bioinformatician, the selected candidate will be involved in multiple projects at a time carrying out daily responsibilities in data analysis, storage, and maintenance; work in collaboration with the diverse team of researchers to provide assistance in experimental design; aid in optimization of existing computational workflows and incorporation of new methodologies as needed; deliver interpretable and actionable results providing new hypotheses and identifying most promising targets for future experiments.



Duties and responsibilities



  • Storage and maintenance of raw data including but not limited to microarrays, sequencing of various RNA species, CHiP-seq, ATAC-seq, quantitative proteomics, and DNA methylation sequencing

  • Primary analysis workflows including demultiplexing, read trimming, read quality assessment, alignment and feature quantification for datasets drawn from multiple platforms including mRNA-seq, microRNA-seq, CHiP-seq, ATAC-seq

  • Secondary analyses of processed data including expression profiling (hierarchical clustering, PCA), identification of differentially regulated genes and pathways, functional annotation, miRNA target identification, and transcription factor binding site prediction

  • Providing bioinformatics support and training to the research team including assistance in the analysis and interpretation of biological datasets and recommendation of best practices for experiments involving next generation sequencing technologies

Necessary qualifications



  • PhD in bioinformatics, biotechnology, computational biology, molecular neurobiology, or a related field

  • Excellent skills in statistical programming and data visualization in R and Bioconductor (DESeq2, edgeR, RUVSeq, LIMMA)

  • Excellent skills in Python programming

  • Extensive experience with software tools for various next generation sequencing tasks including quality control and preprocessing (FastQC, trimmomatic, samtools), read alignment (Subread, Bowtie2, STAR) and quantification (HTSeq, featureCounts), and peak calling for CHiP-seq and ATAC-seq data (macs2)

  • Experience with small RNA target prediction (TargetScan, miRbase, TarBase)

  • Experience with integrative analysis of data drawn from multiple sequencing platforms and levels

  • Experience in pipeline development via Python or Perl programming languages

  • Experience in UNIX/Linux environment and shell scripting

  • Strong knowledge of statistics, linear model building, principal component analysis, and factor analysis

  • Experience with functional annotation tools and databases such as GSEA, Gene Ontology, Ingenuity Pathway Analysis, ToppCluster, KEGG, and DAVID

  • Experience with analysis of microarray platforms such as U133 and HuGene2

  • Keen interest in underlying biology, neuroscience, and disease modeling

  • Excellent English writing and communication skills

  • Demonstrated ability to distill vast amounts of biological data into interpretable and actionable results that could serve in generating new hypotheses, defining future avenues of research and identifying potential new therapeutic targets



    The position is available for 1 year with the possibility of subsequent extension and longer-term appointment.

Application deadline



15 May 2018



Please include:

  • Cover letter

  • Curriculum vitae illustrating relevant experience

  • Full contact details of 3 references

  • A PhD Diplomas and Master of Science certificate



For further information, please contact the center’s administrator Ann Christensen, ann.christensen@sund.ku.dk.







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