Summary
The Control Theory and Systems Biology Laboratory at ETH Zürich invites applications for doctoral positions focused on integrating control theory, stochastic dynamics, and machine learning within synthetic biology. Funded by a European Research Council (ERC) Advanced Grant, candidates will engage in cutting-edge research aimed at developing mathematical and computational frameworks for engineering biological feedback systems.
Doctoral Positions in Control, Stochastic Dynamics, and Machine Learning for Synthetic Biology, ETH Zürich, Switzerland
Designation
Doctoral Researcher
| Field | Details |
|---|---|
| Research Area | Control Theory, Stochastic Dynamics, Machine Learning, Synthetic Biology |
| Location | ETH Zürich, Switzerland |
| Eligibility/Qualification | Candidates with a Master’s degree in applied mathematics, control theory, machine learning, or related fields. Strong preparation in dynamical systems, probability, optimization, or computational methods is essential. Experience in biology or synthetic biology is welcome but not required. |
Job Description
The successful candidate will:
- Conduct research on mathematical modeling, analysis, and design of biomolecular dynamical systems.
- Focus on control-theoretic design and analysis of biomolecular feedback circuits.
- Explore stochastic modeling and biochemical reaction networks.
- Implement learning-based approaches for biochemical dynamical system analysis and design.
- Integrate machine learning with mechanistic models of biochemical dynamics.
How to Apply
Interested candidates should submit the following documents through the online application portal:
- Curriculum vitae
- Academic transcripts
- A short statement of motivation and research interests
- Contact information for three references
Note: Applications sent via email or postal services will not be considered.
Last Date to Apply
Applications received by 30 April 2026 will receive full consideration; positions will remain open until filled. Start date is set for Fall 2026 (flexible).
For more information about the department and to apply, please visit the ETH Zürich official website.
