PhD Position in Decoding Environmental History from Microorganisms for Living Sensors and Memory

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

PhD Position in Decoding Environmental History from Microorganisms for Living Sensors and Memory: Help pave the future for living sensing systems by decoding microorganisms' encoding of environmental history.

• Salary range: €3204 - €4051
• Hours per week: 38-40
• FTE: 1,0

Job description

Background:

Living microorganisms could transform how we sense and store information, replacing single-use electronics with inherently biodegradable systems that track environmental conditions over time. Even basic electronic sensing systems today require sensors, microcontrollers, memory, and batteries, and are often disposable. For example, temperature and humidity dataloggers used during food and vaccine transport become e-waste within weeks. Meanwhile, many species of microorganisms, such as the iridescent Flavobacteria, integrate environmental signals and store history structurally, all with minimal energy. Readout may be as simple as taking a photograph. Could these organisms replace conventional electronics and enable fully degradable, battery-less dataloggers? What's missing in realizing this future is our ability to interpret this biological record: we do not yet understand what the visual characteristics of organisms represent quantitatively, or how reliably we can recover that information.

This PhD:

We are seeking a highly motivated PhD student to play a formative role in understanding how to decode environmental information from living microorganisms, in pursuit of living sensing and memory systems. This effort is truly trans-disciplinary, drawing on biodesign/biotechnology, machine learning, and interaction design. This project builds on groundwork already underway in our group but is meant to be shaped substantially by the candidate's own interests and expertise.

The candidate will cultivate the living organism itself, characterize and model its visible responses to different environmental conditions, and develop and validate computational decoders that recover environmental history from an image of the living organism. Based on the found capabilities, the candidate will also design prototypes that incorporate living sensors, such as fully compostable, smart packaging for temperature and humidity monitoring for food, vaccines, or archival documents.

The PhD candidate will be situated at the intersection of the Knowledge and Intelligent Design group and the Materializing Futures group in Sustainable Design Engineering (SDE), a department within the Faculty of Industrial Design Engineering.

Job requirements

We look for candidates who have:

• A Master's degree (or equivalent) in Computer Science, Electrical Engineering, Biodesign, Design Engineering, or a related field
• Experience in building and deploying machine learning or computer vision models
• Technical competencies in one or more of the following: bio-digital systems, biodesign, applied machine learning, computer vision, computational biology, and/or physical prototyping
• Experience or strong interest in biodesign and hands-on interaction with living organisms
• Experience or interest in conducting research with sound experimental design
• Ability to work in a multidisciplinary team, communicate effectively, and take initiative
• Prior publications and experience presenting at international conferences are assets but not requirements

Doing a PhD at TU Delft requires English proficiency at a certain level to ensure that the candidate is able to communicate and interact well, participate in English-taught Doctoral Education courses, and write scientific articles and a final thesis.

TU Delft (Delft University of Technology)

At TU Delft, you will have the opportunity to take the initiative, work with others, and grow as a professional. Working at TU Delft means joining an international community of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward.

Faculty Industrial Design Engineering

This is the focus of the Faculty of Industrial Design Engineering (IDE): matching the evolution of people with the speed of the revolution of technology. Delft designers act as a bridge between advances in technology and the needs of people, organisations and society to create products, services and systems with purpose.

IDE is a leader in design research across the application areas of mobility, sustainability and health, as well as its development of design tools and methods. A 350-strong research team and over 2,000 students work together in our inspiring hall, labs and studios.

In close cooperation with industry, the public sector and NGOs we rehearse possible futures in research and education to design for a complex future.

Conditions of employment

Doctoral candidates will be offered a 4-year period of employment in principle, but in the form of 2 employment contracts. An initial 1,5 year contract with an official go/no go progress assessment within 15 months. Followed by an additional contract for the remaining 2,5 years assuming everything goes well and performance requirements are met.

Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from Promovendus gross per month, from the first year to the fourth year based on a fulltime contract (38 hours), plus 8% holiday allowance and an end-of-year bonus of 8.3%.

As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.

The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.

Will you need to relocate to the Netherlands for this job? TU Delft is committed to make your move as smooth as possible. The HR unit, Coming to Delft Service, offers information to help you prepare your relocation. In addition, Coming to Delft Service organises events to help you settle in the Netherlands and expand your social network in Delft. A Dual Career Programme is available to support your accompanying partner with their job search in the Netherlands.

Knowledge security

As part of knowledge security, TU Delft conducts a risk assessment during the recruitment of personnel to prevent the unwanted transfer of sensitive knowledge and technology. The assessment is based on information provided by the candidates themselves, such as their motivation letter and CV, and takes place at the final stages of the selection process. When the outcome of the assessment is negative, the candidate will be informed.