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UNUniversitätsklinikum Köln AöR

Bioinformatician / Computational Biologist(m/w/x)

Köln
Full-timeOn-site
Data Science

Analyzing next-generation sequencing data from pediatric tumors, integrating molecular types, and single-cell/spatial transcriptomics. Strong programming and large-scale biological data analysis skills required. Regular working hours, company pension schemes.

Requirements

  • University degree in bioinformatics, computational biology, computer science, mathematics, physics, or related discipline
  • Advanced degree (M.Sc. or Ph.D.) or Bachelor's with substantial research experience
  • Strong experience in high-throughput sequencing data analysis (genomic, transcriptomic)
  • Solid programming and data analysis skills, experience with large-scale biological data
  • Genuine interest in cancer biology and pediatric oncology research
  • Experience with spatial transcriptomics or related spatial genomics technologies (highly desirable)
  • Good communication skills and ability to drive scientific projects independently
  • University degree in bioinformatics, computational biology, computer science, mathematics, physics, or related discipline
  • Advanced degree (M.Sc. or Ph.D.) or Bachelor's with substantial research experience
  • Strong experience in high-throughput sequencing data analysis (genomic, transcriptomic)
  • Solid programming and data analysis skills, experience with large-scale biological data
  • Genuine interest in cancer biology and pediatric oncology research
  • Experience with spatial transcriptomics or related spatial genomics technologies (highly desirable)
  • Good communication skills and ability to drive scientific projects independently

Tasks

  • Analyze large-scale next-generation sequencing datasets from pediatric tumor samples
  • Develop and implement computational workflows and analysis pipelines
  • Integrate different molecular data types
  • Analyze single cell sequencing data
  • Analyze spatially resolved transcriptomics data
  • Investigate tumor heterogeneity and tumor microenvironment interactions
  • Contribute to data interpretation and visualization
  • Develop novel analytical concepts for complex cancer genomic datasets
  • Collaborate with experimental and clinical researchers
  • Interact closely with the Department of Translational Genomics

Education

  • Bachelor's degreeOR
  • Master's degree

Languages

  • EnglishBusiness Fluent

Tools & Technologies

  • C++
  • R
  • Python
  • high-throughput sequencing data analysis
  • genomic data analysis
  • transcriptomic data analysis
  • large-scale biological data analysis
  • spatial transcriptomics
  • spatial genomics technologies

Benefits

Retirement Plans

  • Company pension schemes

Other Benefits

  • Numerous support options

Learning & Development

  • Extensive training opportunities
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