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Postdoctoral Fellow
Postdoc – Lab Automation and Data-Driven Colloid Science Full-time NEW
Postdoctoral Research Fellow (m/f/d) – Lab Automation and Data-Driven Colloid Science
The Chair of Complex Soft Matter at the TUM School of Life Sciences Weihenstephan is seeking to appoint a Postdoctoral Research Fellow (m/f/d) – Lab Automation and Data-Driven Colloid Science as soon as possible
The Chair of Complex Soft Matter at the TUM School of Life Sciences is seeking to appoint a Postdoctoral Research Fellow (m/f/d) – Lab Automation and Data-Driven Colloid Science at the earliest possible date. The position offers the opportunity to play a central role in establishing next-generation automated research infrastructure and methodologies for closed-loop, data-driven experimentation in colloid science. The successful candidate will contribute to the development of self-driving laboratory capabilities integrating robotics, high-throughput experimentation, quantitative characterization, and machine learning-enabled decision-making. The position is associated with the recently awarded ERC Consolidator Grant project “Engineering Multivalency for Superselective Recognition of Pathogen Targets” (EngToTarget), offering a unique opportunity to contribute to emerging approaches in autonomous experimentation, colloid science, and AI-driven materials research.
About Us:
The Technical University of Munich (TUM) is one of Europe’s leading academic institutions. At the TUM School of Life Sciences, Prof. Stefan Guldin recently established the Chair of Complex Soft Matter. We focus on understanding and controlling the formation and interactions of soft materials at the nanoscale using principles of molecular self-assembly. We harness a broad range of building blocks – including polymers, biomolecules, vesicles, and nanoparticles – to engineer colloidal systems and interfaces with targeted functionality and selective molecular recognition. In parallel, we develop advanced characterization techniques, automation workflows, and data-driven methodologies through open-source software and hardware development. Current activities include autonomous experimentation, robotic synthesis platforms, high-throughput materials screening, and machine learning-assisted analysis of complex colloidal systems, with applications spanning healthcare, environmental technologies, food science, and sustainable materials engineering.
Your Responsibilities:
• Develop and implement automated experimental workflows for soft matter and colloidal systems, including robotic liquid handling, high-throughput sample preparation, and integrated characterization approaches
• Contribute to the establishment of self-driving laboratory infrastructure for closed-loop and adaptive experimentation, integrating robotics, data acquisition, statistical analysis, and machine learning-enabled decision-making
• Prototype, integrate, and optimise suitable open-source hardware and software solutions for automated experimentation, including laboratory instrumentation, sensors, and custom-built research tools
• Develop robust and reproducible methodologies for automated synthesis, formulation, and characterization workflows, including meticulous documentation of experimental protocols, software pipelines, and laboratory procedures
• Contribute to data-driven approaches for predictive colloid science, including experimental design, data analysis, modelling, and machine learning-assisted optimisation of complex experimental systems
• Work closely with researchers across materials science, chemistry, life sciences, and data science in a highly interdisciplinary environment
• Contribute to scientific publications, conference presentations, grant development, and dissemination activities
• Support and mentor doctoral, master’s, and undergraduate researchers within the group
Your Profile:
• PhD in chemistry, materials science, chemical engineering, mechanical engineering or a related discipline
• Strong experimental and/or computational background in laboratory automation, robotics and autonomous experimentation, ideally including experience with robotic liquid handling, hardware integration, or experimental workflow development
• Experience with scientific programming and data analysis, ideally using Python-based tools and frameworks, with familiarity in areas such as statistical modelling, machine learning, computer vision, or optimisation approaches for experimental systems
• Experience with rapid prototyping, CAD design, electronics integration, sensor systems, or open-source hardware development is beneficial
• Interest in soft matter, colloid science, self-assembly, biointerfaces, or advanced materials characterization techniques is desirable
• Strong problem-solving abilities, hands-on experimental mindset, and enthusiasm for interdisciplinary research at the interface of materials science, automation, and AI-driven experimentation
• Ability to work independently while contributing effectively within an international and collaborative interdisciplinary research environment
• Excellent written and verbal communication skills in English
What We Offer:
• The opportunity to help establish a next-generation research environment for automated and data-driven colloid science, with access to advanced characterization techniques, automation platforms, and emerging self-driving laboratory infrastructure
• Participation in a highly interdisciplinary and internationally visible research programme combining colloid science, nano-bio interfaces, robotics, and data-driven experimentation
• Significant scientific freedom to shape research directions, methodologies, and platform development within a rapidly growing area of the group
• A clear perspective for development towards a group leader position within the emerging research area of autonomous and data-driven colloid science, including opportunities to build an independent scientific profile, initiate collaborative projects, contribute to grant development, and support the supervision of junior researchers
• A collaborative, ambitious, and supportive international team environment with opportunities for professional development, international collaboration, and career progression
• Salary according to TV-L, initially limited to 24 months with the possibility of extension subject to performance and funding availability
Application:
This position is suitable for individuals with severe disabilities. Applicants with severe disabilities will be given preference if their qualifications, skills, and professional performance are otherwise essentially equal.
TUM is committed to increasing the proportion of women in its workforce; applications from women are therefore expressly encouraged.
Please submit your complete application documents as a single PDF file by 21 June 2026 to admin.cosmat@ls.tum.de. For informal inquiries, please contact: Prof. Stefan Guldin guldin@tum.de
We appreciate your interest in the Technical University of Munich and your application for the advertised position. By submitting your application, you have provided us with personal data. Please note our privacy notice pursuant to Article 13 of the General Data Protection Regulation (GDPR) regarding the collection and processing of personal data in connection with your application, available at https://portal.mytum.de/kompass/datenschutz/Bewerbung/.
Data Protection Information:
When you apply for a position with the Technical University of Munich (TUM), you are submitting personal information. With regard to personal information, please take note of the Datenschutzhinweise gemäß Art. 13 Datenschutz-Grundverordnung (DSGVO) zur Erhebung und Verarbeitung von personenbezogenen Daten im Rahmen Ihrer Bewerbung. (data protection information on collecting and processing personal data contained in your application in accordance with Art. 13 of the General Data Protection Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM.
Kontakt: admin.cosmat@ls.tum.de