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We develop robust optofluidic experiments that use light-driven flows to manipulate cells and microscopic objects. Our next step is to connect these platforms with AI agents - potentially including Hermes-like tool-using agents and multi-agent systems - to plan experiments, operate instruments, analyse outcomes and improve subsequent actions. Help us turn reliable laboratory hardware into autonomous scientific discovery systems.

Your role

• Develop and integrate tool-using AI agents and multi-agent workflows with established optofluidic and microscopy setups.
• Build robust Pythosn interfaces, APIs and instrument-control services for acquisition, actuation and experimental feedback.
• Combine quantitative image analysis, machine learning, feedback control and optimisation to enable adaptive experiments and autonomous scientific data generation.
• Develop experimental planning and agent evaluation with safeguards, logging, reproducible protocols and systematic handling of failures.
• Work with an interdisciplinary team and publish new methods and scientific results in biophotonics and Physical AI.

• PhD in physics, biophysics, mechatronics, robotics, engineering, computer sciences or related field.
• Strong Python programming skills, quantitative and mathematical reasoning and experience developing or automating scientific systems.
• Experience in at least one of laboratory automation, instrument control, robotics, computer vision, feedback control, biophysics or machine learning.
• Solid analytical skills, independent problem-solving, collaborative mindset and excellent English communication.
• Interest in agentic AI, autonomous experimentation and scientific discovery; experience with LLM-based agents, MCP/API tools or multi-agent systems is a plus - not a prerequisite.
• Optics or biophotonics experience is welcome but not required: outstanding candidates from adjacent fields are encouraged to apply.