Scientific activities / projects, PhD position

Development of novel methods for leveraging modern data storage technologies in data-intensive sciences

Starting date


Duration of contract

3 years


up to the German TVöD 13

Type of employment


At the Institute of Data Science in Jena in the research group on „Data Management Technologies“ we develop novel methods and techniques for storing, managing, describing, and processing large amounts of multi-dimensional data (e.g., data from earth observation and radio astronomy) in distributed storage systems. The work is conducted in close collaboration with the German Remote Sensing Data Center and external partners at the Thüringer Landessternwarte Tautenburg and the Max Planck Institute for Radio Astronomy. Your task is to develop novel methods for integration of modern data storage technologies, such as, shingled disks (SMR), zoned namespaces (ZNS), and computational storage devices in the context of the H2020 EU project DAPHNE. You are responsible for the conception of scientific methods for incorporating modern data storage technologies into data infrastructures in data-intensive sciences, such as, earth observation and radio astronomy. Leveraging modern data storage hardware efficiently is a nontrivial research task and requires advanced knowledge of data management technologies using modern computer hardware and tiered storage systems. Additionally, it requires intensive coordination with our international partners in the context of the H2020 EU project DAPHNE. The position allows obtaining a PhD degree at a collaborating university.

The emphasis of your activities will be on:

  • Analysis of core requirements for the management of large, complex scientific data sets in tiered, distributed data storage systems
  • Literature research in the area of large-scale data management & data storage technologies for multi-dimensional data with the goal to compare existing and develop new methods and techniques
  • Analysis of current IT architectures and systems and their usage for the development of novel methods of data management & data storage of multidimensional data from data-intensive sciences
  • Development of innovative concepts for data storage and processing of large data volumes from data-intensive sciences
  • Development of efficient, scalable algorithms and data structures for storing and processing large volumes of scientific data
  • Integration & testing of developed software modules
  • Scientific evaluation, documentation, and publication of results in scientific journals, workshops, or conferences
  • Oral presentation of scientific results at national and international conferences/events
  • Technical supervision of undergraduate students
  • Reviewing student theses
  • Hands-on support for new colleagues into the developed software modules
  • Contribution to the management, documentation, and maintenance of IT platforms

Your qualifications:

  • Completed academic degree in computer science or comparable engineering field of study (university diploma / master’s degree)
  • Some experience in working independently and autonomously on complex research questions
  • Proven practical experience in data management & processing of large data volumes (in particular data storage & processing)
  • Proven practical experience in performance-oriented programming (e.g., C/C++, Rust) by leveraging modern hardware
  • Fluency in written and oral English
  • Advanced knowledge in database implementation techniques (e.g., index structures or storage managers) is a plus
  • Advanced knowledge of the Linux I/O stack and modern data storage technologies (e.g., SSDs, SMR disks, tiered storage, computational storage) is of advantage
  • Fluency in written and oral German is a plus

Your benefits:

Look forward to a fulfilling job with an employer who appreciates your commitment and supports your personal and professional development. Our unique infrastructure offers you a working environment in which you have unparalled scope to develop your creative ideas and accomplish your professional objectives. Our human resources policy places great value on a healthy family and work-life-balance as well as equal opportunities for persons of all genders (m/f/non-binary). Individuals with disabilities will be given preferential consideration in the event their qualifications are equivalent to those of other candidates.

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Technical contact

Dr. Marcus Paradies
Institute of Data Science

Phone: +49 3641 30960-103

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Vacancy 50110

HR department Berlin

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DLR site Jena

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DLR Institute of Data Science

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