Postdoc in Computational Biology/Bioinformatics: Proteomics & Complex Data

Charité Berlin (ImmunoPreCept Cluster of Excellence)
We are looking for a motivated computational biologist / bioinformatician with a strong interest in quantitative biology and mass spectrometry-based proteomics to develop new approaches for extracting biological information from complex mass spectrometry datasets.
You will work with unique large-scale datasets (including microbial communities, gut microbiomes, patient cohorts, and yeast libraries) to investigate proteomic variation in complex biological samples. We are therefore particularly interested in candidates who understand how mass spectrometry data are generated and processed, and how experimental design, sample complexity, instrument acquisition and data processing influence the resulting quantitative data.

What you’ll do

• Generate systematic proteomic datasets as part of a collaborative team effort
• Develop and apply statistical and quantitative approaches to extract biological
  information from high-dimensional data
• Integrate proteomics data with biological (e.g. genomics) data and clinical information
• Collaborate closely with mass spectrometry experts, experimental scientists and
  clinicians

  What we’re looking for

  • PhD in bioinformatics, computational biology, or related field
  • Experience in analyzing biological data, especially proteomics data
  • Strong knowledge of statistical and quantitative methods for analyzing complex, highdimensional datasets
  • Good understanding of biochemical principles, including mass spectrometry
  • Good programming skills (Python and/or R)
  • Strong communication skills, ability to work in interdisciplinary teams, and proven publication track record
  • Ability to work independently while collaborating across research groups

    Why join us

    • Work with exceptional large-scale datasets and cutting-edge mass spectrometry
      technologies
    • Opportunity to combine method development, statistics and biological discovery
    • Be part of a highly collaborative, interdisciplinary team, whilst having a high degree of
      scientific independence
    • Contribute to translational research
    • Comprehensive training and professional development opportunities
    • Excellent track record of alumni progressing to independent group leader roles and
      leadership positions in industry