Group Leader in AI-Assisted Autonomous Experimentation

The new group will broadly leverage DIFFER's state-of-the-art infrastructure, including material synthesis platforms (VSParticle Nanoparticle Printer, Pulsed Laser Deposition), advanced analytical instrumentation (XRD, SEM, TEM, XRF, XPS), and automated chemical characterization tools (electrochemical workstations, ICP-MS, GC-MS), to enable transformative advancements in autonomous materials discovery.

The successful candidate will lead the development of integrated frameworks for automating a variety of experimental workflows. You will focus on connecting relevant laboratory setups and experimental design with advanced AI-driven methods to enable automation in electro-, thermo-, or plasma-driven energy carrier conversion experiments.

The Group Leader is expected to create pioneering solutions to seamlessly integrate diverse laboratory equipment and robotics, establishing fully automated experimental workflows, and implementing AI-assisted adaptive experiment planning supported by real-time data analytics. This role involves collaboration with researchers and engineers for the design of robust, FAIR-compliant data infrastructures capable of handling large-scale, real-time experimental data. The Group Leader will also play a central role in translating insights from digital twin simulations, currently under development at DIFFER, into the design and optimization of real-world experimental workflows.

We seek an outstanding scientist or engineer experienced in building automated laboratories with integrated lab equipment and handling complex experimental workflows. The ideal candidate has demonstrated experience integrating laboratory automation, machine learning-driven optimization, and high-throughput experimentation in materials science, chemistry, physics, or related fields, and has contributed to collaborative projects at the forefront of AI-assisted experimentation.

Responsibilities:

• Lead the establishment and management of an integrated autonomous experimentation platform, combining advanced synthesis, material and chemical characterization equipment into a unified, automated system.
• Develop and implement AI-driven methodologies for autonomous, adaptive experimentation – including active learning algorithms and self-optimizing experimental workflows – ensuring effective integration across heterogeneous instruments.
• Contribute to the development of a robust data infrastructure adhering to FAIR data principles, enabling real-time data acquisition, analysis, and decision-making to accelerate discovery.
• Apply insights from digital twin simulations developed by colleagues to improve the design of physical laboratory setups and experimental workflows.
• Collaborate closely with materials scientists, chemists, and engineers to ensure effective integration of synthesis and characterization techniques, and AI tools into the self-driving lab framework.
• Secure external research funding through competitive grants and industrial partnerships to expand the capabilities and impact of the group’s research.
• Supervise PhD students, postdoctoral researchers, and engineers, promoting scientific excellence and career development.
• Disseminate research findings through publications, presentations, and stakeholder engagement activities.

Requirements

Requirements:

• PhD in computer science, materials science, chemistry, physics, mechanical engineering, electrical engineering, or a related discipline, with a strong focus on automation, robotics, or AI-driven experimental methods.
• Proven hands-on experience in developing and implementing automated experimental workflows, including the integration of robotics.
• Demonstrated excellence in research, evidenced by a record of high-impact publications, patents, or other significant scientific contributions.
• Proven ability to attract and manage competitive research funding, and to build collaborative projects with academic and/or industrial partners.
• Strong leadership, project management, and collaborative skills.
• Excellent proficiency in English.

At DIFFER, we value scientific passion, collaboration, inclusivity, and leadership. Candidates are expected to uphold professionalism, openness, and respect, contributing to a positive and productive research environment. We offer world-class research facilities, along with extensive opportunities for professional development, and a collaborative environment for groundbreaking research.

Contract terms

We offer a permanent, full-time position (1.0 FTE) with a competitive gross salary starting in scale 13 (€6,299–€7,672 monthly) and the possibility of progression to scale 14 (€6,613–€8,424) after two years upon positive performance. You will also receive an 8% holiday allowance and an 8.3% year-end bonus, and benefit from excellent secondary employment conditions including generous leave entitlements, a solid pension scheme, and partially paid parental leave.

The position will be based at DIFFER () and the working location will be at TU Eindhoven. When fulfilling a position at DIFFER, you will have an employee status at NWO. You can participate in all the employee benefits NWO offers. We have a number of regulations that support employees in finding a good work-life balance. At DIFFER we believe that a workforce diverse in gender, age and cultural background is key to performing excellent research. We therefore strongly encourage everyone to apply. More information on working at NWO can be found at the NWO website ()