PhD in Living Sensors: Decode Microbial Env History

Delft University of Technology; Delft; On-site; EUR 36,000 - 45,000; Full time

Benefits offered by this job

Relocation support

Health insurance discount

Monthly work costs contribution

Job summary

Delft University of Technology offers a PhD position focused on decoding environmental history from living microorganisms for sensing and memory systems. The project spans biodesign, machine learning, and interaction design, and invites candidate-driven shaping of the research direction.

The PhD candidate will grow the living organism, model its responses, and develop decoders to extract environmental history from images, with potential prototypes for compostable sensing packaging.

Qualifications

• Master's degree or equivalent in CS, EE, Biodesign, Design Engineering or related field.
• Experience in building and deploying ML or CV models.
• Competencies in bio-digital systems, biodesign, ML, CV, computational biology or prototyping.
• Experience with living organisms and sound experimental design.

Responsibilities

• Cultivate the living organism and characterize its responses to environmental conditions.
• Develop and validate computational decoders that recover environmental history from images.
• Model the organism's visible responses and build predictive frameworks.
• Design prototypes with living sensors, e.g., compostable smart packaging for monitoring conditions.

Skills

Machine learning

Computer vision

Biodesign

Interdisciplinary teamwork

Experiment design

Education

Master's degree in CS/EE/Biodesign/Design Engineering

Tools

TensorFlow / PyTorch

Job description

Delft University of Technology offers a PhD position focused on decoding environmental history from living microorganisms for sensing and memory systems. The project spans biodesign, machine learning, and interaction design, and invites candidate-driven shaping of the research direction.

The PhD candidate will grow the living organism, model its responses, and develop decoders to extract environmental history from images, with potential prototypes for compostable sensing packaging.