PhD in Metabolic Flux Analysis: The Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE) is offering a PhD position focused on developing a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism. This project seeks to utilize advanced computational techniques to enhance methods for metabolic flux analysis.
PhD Scholarship Opportunity in Probabilistic Metabolic Flux Analysis
Designation
PhD Candidate
| Research Area | Location | Eligibility/Qualification |
|---|---|---|
| Probabilistic Metabolic Flux Analysis | Forschungszentrum Jülich, Germany | Excellent Master’s in statistics, physics, mathematics, or related field; strong programming skills in Python and C++; familiarity with Bayesian techniques desirable. |
Description
The PhD project will involve the design of hierarchical models that capture model misspecifications in metabolic models, development of differentiable and scalable inference algorithms, implementation of HPC-tailored sampling strategies, and application of frameworks to real biological datasets. The successful candidate will also contribute to open-source software tools and present findings at international conferences. Benefits include a supportive international environment, mentorship, and professional development opportunities.
How to Apply
Interested candidates should submit their applications via the official HDS-LEE website. For detailed information on the application process, please refer to the FAQs section on the website.
Last Date to Apply
Applications accepted until the position is filled. It is recommended to apply as soon as possible.
