Your Job:

This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis.

You will:

• Design hierarchical models that explicitly capture misspecifications in metabolic models
  
• Develop differentiable and scalable inference algorithms using automatic differentiation
  
• Implement HPC-tailored sampling strategies in Python and C++
  
• Apply your framework to analyse real biological datasets to demonstrate robustness, interpretability, and practical impact
  
• Contribute to open-source software tools, helping to shape future research infrastructure
  
• Present your results on conferences in Germany and abroad

Your Profile:

• Excellent Master’s degree in statistics, physics, mathematics, or a related quantitative field, ideally with a strong focus on computational practice
  
• Strong mathematical and statistical background, with pronounced analytical and problem-solving skills
  
• Proven programming expertise in Python and C++, with solid experience in scientific computing and software development; familiarity with Linux environments
  
• Excellent collaboration and communication skills and enjoyment of working in an international, interdisciplinary research team
  
• Familiarity with Bayesian thinking is desirable
  
• No prior biological experience is required; curiosity for life science questions and willingness to collaborate with experimentalists is sufficient
  
• Prior research experience (e.g. internships, thesis projects, open-source contributions, or publications) is highly desirable
  
• Knowledge of German is beneficial

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 with strong links to DLR Cologne and RWTH Aachen. We offer ideal conditions for you to complete your doctoral degree:

• Outstanding scientific and technical infrastructures
  
• Working in an international and interdisciplinary environment at one of Europe’s largest research institutes
  
• Continuous scientific mentoring by your scientific advisors and opportunity to mentor students
  
• Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/
  
• A qualification that is highly valued in industry
  
• 30 days of annual leave and flexible working arrangements, including partial remote work.
  
• Further development of your personal strengths, e.g. via a comprehensive 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: https://www.fz-juelich.de/judocs
  
• Targeted services for international employees, e.g. through our International Advisory Service
  

The position is limited to three years, with a possible one-year extension. Pay is in line with 75% 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"). The monthly salaries in euro can be found on the BMI website: https://go.fzj.de/bmi.tvoed.entgelt

Further information on doctoral degrees at Forschungszentrum Jülich (including its various branch offices) is available at https://www.fz-juelich.de/en/careers/phd

We welcome applications from people with diverse backgrounds, e.g. in terms of age, gender, disability, sexual orientation / identity, and social, ethnic and religious origin. A diverse and inclusive working environment with equal opportunities in which everyone can realize their potential is important to us.

The following links provide further information on diversity and equal opportunities: https://go.fzj.de/equality and on specific support options for women: https://go.fzj.de/womens-job-journey