Doctoral Positions in Control, Stochastic Dynamics, and Machine Learning for Synthetic Biology
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Doctoral Positions in Control, Stochastic Dynamics, and Machine Learning for Synthetic Biology
100%, Basel, fixed-term
The Control Theory and Systems Biology Laboratory at ETH Zürich (Prof. Mustafa Khammash) invites applications for one or more doctoral positions at the interface of control theory, stochastic dynamical systems, and machine learning, with applications to synthetic biology and biomolecular circuit design.
Our research develops mathematical and computational frameworks for understanding and engineering biological feedback systems, including biomolecular controllers, stochastic biochemical reaction networks, and programmable cellular circuits. The successful candidate will contribute to the development of new theoretical and computational methods for the analysis and design of biological dynamical systems. The positions are funded by a European Research Council (ERC) Advanced Grant. The successful candidate will join an interdisciplinary team of theorists and experimentalists working on the analysis and design of programmable biological systems, with applications to cell-based therapies.
Job description
The candidate will conduct state-of-the-art research on the mathematical modeling, analysis, and design of biomolecular dynamical systems, at the interface of control theory, stochastic dynamics, and machine learning. Possible research directions include:
- Control-theoretic design and analysis of biomolecular feedback circuits
- Stochastic modeling and analysis of biochemical reaction networks and cellular noise
- Learning-based approaches for the analysis and design of biochemical dynamical systems (including reinforcement learning and generative AI)
- Integration of machine learning with mechanistic models of biochemical dynamics
Profile
- The position is suited for candidates with a strong background in applied mathematics, control theory, machine learning, statistical physics, or related disciplines
- Applicants should hold (or expect to receive) a Master’s degree in a relevant field and have strong preparation in dynamical systems, probability, optimization, or computational methods
- Prior experience in biology or synthetic biology is welcome but not required
- Candidates with strong mathematical or computational backgrounds and an interest in biological systems are strongly encouraged to apply
- In addition to the technical skills, the candidate is expected to have social and leadership competencies needed for a positive work culture including acting responsibly, nurturing well-being, driving innovation, living inclusivity, building bridges, and enabling people
Workplace
Workplace
We offer
- A stimulating, supportive, and international research environment at ETH Zurich
- The opportunity to contribute to cutting-edge research at the interface of control engineering, synthetic biology and medicine
- Access to state-of-the-art facilities and world-class collaborators
- We are actively committed to a sustainable and climate-neutral university
- You can expect numerous benefits, such as public transport season tickets and car sharing, a wide range of sports offered by the ASVZ, childcare and attractive pension benefits
We value diversity and sustainability
Curious? So are we.
We look forward to receiving your online application with the following documents:
- Curriculum vitae
- Academic transcripts
- A short statement of motivation and research interests
- Contact information for three references
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
Applications received by 30 April 2026 will receive full consideration. The positions will remain open until filled.
Start date: Fall 2026 (flexible).
Further information about the department can be found on our website.