Forschungszentrum Jülich
Just Landed
Posted Yesterday
Master Thesis in Efficient Markov Chain Monte Carlo Techniques for Large-scale Metabolic Models Forschungszentrum Jülich GmbH in Germany
Degree Level
Master's
Field of study
Computer Science
Funding
The thesis is paid with a reasonable remuneration; no stipend amount or tuition details are given.
Country
Germany
University
Forschungszentrum Jülich

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.
Apply for this position
Keywords
Suggested positions
About this position
Master Thesis opportunity at Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences – Biotechnology (IBG-1), Modeling and Simulation Group.
The project sits at the interface of computational systems biology, mathematics/statistics, and open research software development. The topic is Efficient Markov Chain Monte Carlo Techniques for Studying Large-scale Metabolic Models, with a focus on Bayesian inference for high-dimensional parameter estimation in biochemical networks and metabolic flux inference.
You will develop tailored MCMC algorithms inspired by methods such as differential evolution MCMC and Riemann manifold Langevin Monte Carlo, implement them in an existing C++ framework, and validate/benchmark the methods on a realistic case study. The project can lean more toward mathematical theory, software implementation for Jülich supercomputers (GPU/CPU), or a combined modeling approach.
Eligibility highlights: currently enrolled in a master's degree program; strong motivation; interest in probability theory, mathematics, and data science; very good practical C++ and Python skills; very good English (at least B2 CEFR, ideally certified).
Location: Jülich, Germany. Funding: paid thesis with reasonable remuneration. Deadline: open until filled.
Apply via the online application link in the post. For questions, use the provided contact form or career portal.
Funding details
The thesis is paid with a reasonable remuneration; no stipend amount or tuition details are given.
What's required
Applicants must be currently enrolled in a master's degree program and planning their thesis. Strong motivation and interest in probability theory, mathematics, and data science are required. Very good practical C++ and Python programming skills are expected. Very good written and spoken English at least at B2 CEFR level is required, ideally supported by a certificate. Interest in curiosity-driven multidisciplinary research is preferred.
How to apply
Apply through the online application portal linked in the posting. For questions, use the contact form or career portal provided in the post. Review the application information and FAQ links before submitting.
More information can be found here
Ask ApplyKite AI

How do I apply for this?
Sign in for free to reveal details, requirements, and source links.