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 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 chevron_right Working, teaching and research at ETH Zurich We value diversity and sustainability In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future. 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. About ETH Zürich ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow. Wenn Sie sich auf diese Stelle bewerben, erwähnen Sie bitte dass Sie sie auf Universitoxy gesehen haben.

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

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

chevron_right Working, teaching and research at ETH Zurich

We value diversity and sustainability

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish. Sustainability is a core value for us – we are consistently working towards a climate-neutral future.

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.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science and technology. We are renowned for our excellent education, cutting-edge fundamental research and direct transfer of new knowledge into society. Over 30,000 people from more than 120 countries find our university to be a place that promotes independent thinking and an environment that inspires excellence. Located in the heart of Europe, yet forging connections all over the world, we work together to develop solutions for the global challenges of today and tomorrow.

Wenn Sie sich auf diese Stelle bewerben, erwähnen Sie bitte dass Sie sie auf Universitoxy gesehen haben.

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