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Advertising division: IBG-1 - Biotechnology
Reference number: 2021D-089


You want to apply your data science knowledge to the basic research questions and societal challenges of our modern world? Work with us at the Institute of Bio- and Geosciences - Biotechnology (IBG-1) and our scientists at HDS-LEE at some of the most pressing issues of our time, such as energy transition, climate change and resource scarcity, brain function, drug design, identification of diseases at very early stages. As Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE), we aim to educate and train the next generation of data scientists during their doctoral thesis in close contact to domain-specific knowledge and research in three application domains: Life and medical science, earth science, energy systems and material science.
This HDS-LEE PhD position will be located at the IBG-1 at Forschungszentrum Jülich. The institute investigates how microorganisms and isolated enzymes can be used to produce a variety of products from renewable raw materials. IBG-1 is a leading institution in microbial discovery and process development for industrial biotechnology with increasingly miniaturized and automated experiments. The institute provides an excellent infrastructure for parallelized lab robotic experiments on microtiter plates. The workflow from low temperature storage, cryo-culture, pre-culture and inoculation to main experiments and subsequent cell disruption is currently established. Various methods are available for online and at-line measurements. They are combined with advanced digital technologies for data analysis, experimental design and process optimization. For more information about IBG-1 visit and about HDS-LEE visit

We are looking to recruit a

PhD Position - Automatic Experimentation and Discovery in Bioprocess Development

Your Job:

This project aims at complementing our exceptional experimental platform with digital technologies for data processing, experimental design, workflow management and process control. All components for closing the so-called Design – Build –Test – Learn (DBTL) cycle are available for the existing strain and enzyme libraries, and will be connected in this project. Approaches for data management, Bayesian optimization and Thompson sampling will be established and combined for mixed-integer optimization of strain and process. Process and error models need to be developed that account for biological uncertainty and for system specific causes such as pipetting errors or position effects. In detail, you will

  • Familiarize with our lab robotic platform, process control system and existing computational tools
  • Analyze experimental systems and develop process and error models that account for biological uncertainty and for system specific causes such as pipetting errors or position effects
  • Combine existing approaches for Bayesian optimization and Thompson sampling for mixed-integer optimization of strain and process
  • Solve internal global optimization problems by stochastic and deterministic methods
  • Study descriptors for exploiting similarity between screened strains, enzymes and peptides
  • Evaluate potential of recommender systems for completing sparse information on advantageous process conditions of different strains
  • Apply methods to selected biotechnological systems and research tasks in close collaboration with experimentalists
  • Document code and interfaces, provide tutorials with examples, disseminate results

Your Profile:

  • High interest in applying your data science knowledge to life science
  • Masters degree in physics, mathematics, biotechnology or a related field
  • Good knowledge of machine learning methods
  • Sound experience in at least one programming language (preferably Python and C++)
  • Experience in open source software development is of great advantage
  • Excellent organizational skills and ability to work independently
  • Strong communication skills and capacity to strengthen a highly international and interdisciplinary team
  • High level of scholarship as indicated by bachelor and master study transcripts and two reference letters
  • Very good command of the English language (TOEFL or equivalent evidence)

Our Offer:

We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! This HDS-LEE PhD position will be located at Forschungszentrum Jülich. We offer ideal conditions for you to complete your doctoral degree:

  • Outstanding scientific and technical infrastructure – ideal conditions for successfully completing a doctoral degree
  • A highly motivated group as well as an international and interdisciplinary working environment
  • Continuous scientific mentoring by your scientific advisors
  • Chance of participating in (international) conferences
  • Unique HDS-LEE graduate school program
  • Qualification that is highly welcome in industry
  • Further development of your personal strengths, e.g. via a comprehensive further training program; a structured program of continuing education and networking opportunities specifically for doctoral researchers via JuDocS, the Jülich Center for Doctoral Researchers and Supervisors:
  • Targeted services for international employees, e.g. through our International Advisory Service

The position is initially for a fixed term of 3 years. Pay in line with 100% of pay group 13 of the Collective Agreement for the Public Service (TVöD-Bund) and additionally 60 % of a monthly salary as special payment („Christmas bonus“). Further information on doctoral degrees at Forschungszentrum Jülich including our other locations is available at:

Forschungszentrum Jülich promotes equal opportunities and diversity in its employment relations. We especially foster women in data science and offer individual career planning.

We also welcome applications from disabled persons.

Additional Information

The job will be advertised until the position has been successfully filled. You should therefore submit your application as soon as possible. We look forward to receiving your application via our

Questions about the vacancy?
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Please note that for technical reasons we cannot accept applications via email.