PhD Position in Decoding Environmental History from Microorganisms for Living Sensors and Memory
Join a pioneering project to develop biodegradable living sensing systems.
Best for:Best for candidates with a strong background in computer science or engineering and an interest in biodesign.
Overview
This PhD position focuses on understanding how microorganisms can encode environmental history, potentially replacing conventional electronics with biodegradable alternatives. The candidate will engage in a trans-disciplinary project that combines biodesign, machine learning, and interaction design. Responsibilities include cultivating microorganisms, modeling their responses to environmental changes, and developing computational tools to decode this information. The role is situated within the Knowledge and Intelligent Design group and the Materializing Futures group at TU Delft's Faculty of Industrial Design Engineering.
What you'll do
- Cultivate living microorganisms and study their responses to environmental conditions.
- Develop computational models to decode environmental history from images of microorganisms.
- Design prototypes that utilize living sensors for applications like smart packaging.
- Collaborate with multidisciplinary teams to integrate various fields of study.
- Conduct experiments and analyze data to validate findings.
Requirements
Degree required: Master's degree in Computer Science, Electrical Engineering, Biodesign, Design Engineering, or a related field
Degree offered: PhD
Language: English; proficiency required for participation in Doctoral Education courses
Instruction: English
- Experience in building and deploying machine learning or computer vision models
- Technical knowledge in bio-digital systems or computational biology
- Ability to conduct research with sound experimental design
- Strong communication skills and ability to work in a team
- Candidates must have a Master's degree or equivalent
- No specific nationality or residency requirements mentioned
Funding & terms
How to apply
Deadline: 2026-11-15
Applications should be submitted online before the deadline. Include your CV and cover letter, ensuring no AI-generated content is submitted.
- CV
- Cover letter
Contact
Katherine Song· Supervisor
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