Master Thesis - Efficient Markov Chain Monte Carlo Techniques for Studying Large-scale Metaboli[...]

Master Thesis - Efficient Markov Chain Monte Carlo Techniques for Studying Large-scale Metabolic Models

Join to apply for the Master Thesis - Efficient Markov Chain Monte Carlo Techniques for Studying Large-scale Metabolic Models role at Forschungszentrum Jülich .

Your Job

Our Modeling and Simulation Group offers an interdisciplinary and agile research environment within a dynamic and diverse group. The project exemplifies research at the interface of computational systems biology and mathematics/statistics, with a focus on open research software development. For more information visit or .

Quantifying enzyme activity within large-scale biochemical networks is a key challenge in Systems Biotechnology. Unknown parameters must be inferred from incomplete models and error-prone data. Bayesian analysis using Markov Chain Monte Carlo (MCMC) is the gold standard for such inference problems.

Advanced MCMC methods like differential evolution and Riemann Manifold Langevin Monte Carlo have been proposed for high-dimensional Bayesian inference. However, their direct application to metabolic models is limited due to specific structural challenges.

In this project, you will adapt MCMC methods to metabolic flux inference, develop tailored algorithms inspired by existing approaches, implement them within an existing C++ framework, and validate their performance with real case studies.

The focus can be on mathematical theory, implementation on Jülich supercomputers (GPU/CPU), or integration with practical modeling projects.

Your Profile

• Motivated with an interest in probability theory, mathematics, and data science.
• Strong practical skills in C++ and Python programming.
• Curiosity-driven with an interest in multidisciplinary research.

Our Offer

We work on impactful societal issues and offer you the chance to contribute to meaningful change.

• Engaging and socially relevant thesis topics.
• Practical experience alongside your Master studies.
• Interdisciplinary collaboration in an international, committed team.
• Access to excellent technical equipment and the latest technology.
• Qualified supervision and support.
• Independence in task preparation and execution.
• Flexible working hours and locations.

Additional benefits:

We value diversity and inclusivity, welcoming applicants from all backgrounds to foster an equitable working environment.

Position Details

• Seniority level: Internship

• Employment type: Full-time

• Job function: Education and Training

• Industries: Research

Location: Aachen, North Rhine-Westphalia, Germany