Doctoral Positions in Control, Stochastic Dynamics, and Machine Learning for Synthetic Biology

The Control Theory and Systems Biology Laboratory at ETH Zürich, led by Professor Mustafa Khammash, is offering one or more doctoral positions focused on the intersection of control theory, stochastic dynamics, and machine learning, with direct applications to synthetic biology and biomolecular circuit design. The research group develops advanced mathematical and computational frameworks to understand and engineer biological feedback systems, including biomolecular controllers, stochastic biochemical reaction networks, and programmable cellular circuits. Successful candidates will contribute to the development of new theoretical and computational methods for analyzing and designing biological dynamical systems. Research directions may 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 biochemical dynamical systems (such as reinforcement learning and generative AI), and integration of machine learning with mechanistic models of biochemical dynamics. The positions are funded by a European Research Council (ERC) Advanced Grant, providing salary, benefits, and access to state-of-the-art facilities. Additional benefits include public transport season tickets, car sharing, sports facilities, childcare, and attractive pension options. The research environment at ETH Zürich is stimulating, supportive, and international, offering opportunities to collaborate with world-class researchers and contribute to cutting-edge work at the interface of control engineering, synthetic biology, and medicine. Applicants should hold or expect to receive a Master’s degree in a relevant field such as applied mathematics, control theory, machine learning, statistical physics, or related disciplines. Strong preparation in dynamical systems, probability, optimization, or computational methods is required. Prior experience in biology or synthetic biology is welcome but not mandatory. Candidates with strong mathematical or computational backgrounds and an interest in biological systems are encouraged to apply. Social and leadership competencies, including responsibility, well-being, innovation, inclusivity, and collaboration, are expected. ETH Zürich values diversity, sustainability, and equality of opportunity, fostering an inclusive culture and a climate-neutral future. Applications must be submitted online via the ETH Zürich application portal, including a curriculum vitae, academic transcripts, a short statement of motivation and research interests, and contact information for three references. Applications received by 30 April 2026 will receive full consideration, and the positions will remain open until filled. The anticipated start date is Fall 2026, with flexibility. ETH Zürich is renowned for its excellence in science and technology, offering a vibrant environment for independent thinking and academic excellence. For further information and to apply, visit the provided application link.