Postdoctoral Researcher in Machine Learning and Non-invasive Tumor Profiling

vor 4 Wochen


Heidelberg, Baden-Württemberg, Deutschland Deutsches Krebsforschungszentrum (DKFZ) Vollzeit
Research Opportunity at Deutsches Krebsforschungszentrum (DKFZ)

We are seeking an exceptional bioinformatician/computational scientist to lead our efforts in multimodal tumor profiling at the German Cancer Research Center (DKFZ). The successful candidate will develop integrative analysis approaches to establish disease-relevant signatures using NGS data from liquid biomaterials.

Key Responsibilities
  • Apply machine learning and data analysis techniques to large datasets from liquid biopsies, clinical information, and imaging
  • Process and integrate data from various modalities into harmonized data structures
  • Collaborate with partners at DKFZ, University Hospital of Heidelberg, and national/international collaborators
Requirements
  • Master's degree and PhD in computational biology, bioinformatics, mathematics, physics, computer science, or a related field
  • Previous experience in NGS data analysis and management
  • Experience in big data analysis, machine learning, and modeling is desirable
  • Excellent communication skills in English and German
We Offer
  • State-of-the-art equipment and opportunities for international networking
  • Remuneration according to TV-L incl. company pension scheme and capital-forming payments
  • 30 days of vacation per year
  • Flexible working hours
  • Possibility of mobile work and part-time work
  • Family-friendly working environment
  • Sustainable travel to work: subsidized Germany job ticket
  • Our Corporate Health Management Program offers a holistic approach to your well-being
  • Develop your full potential: access to the DKFZ International Postdoc Program and DKFZ Career Service

We are committed to diversity and inclusion, and welcome applications from talented individuals regardless of gender, cultural background, nationality, ethnicity, sexual identity, physical ability, religion, and age. People with severe disabilities are given preference if they have the same aptitude.



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