PhD Developing AI Tools to Crack the Molecular Basis of Growth and Stress Resilience in Plants

Join us in advancing the frontier of plant sciences and making a tangible impact on agricultural resilience through the power of machine learning!

Job Description

We are seeking a highly motivated PhD candidate to join our interdisciplinary research team focused on enhancing plant resilience using cutting-edge data analysis and machine learning techniques. This exciting opportunity involves developing computational models to investigate growth-stress trade-offs in plants, with a focus on the structure, dynamics, and regulatory roles of protein complexes, particularly patterns of direct and indirect protein–protein interactions involved in signaling and transcriptional regulation.

The candidate will develop machine learning approaches to model how these complexes interact and influence gene expression under diverse stress conditions. Leveraging newly generated multi-omics datasets—including protein interaction profiles, DNA-binding assays, and (single-cell) transcriptomic data—the PhD candidate will explore hybrid modeling strategies that integrate mechanistic representations (e.g., dependency graphs) with data-driven methods (e.g., ensemble predictors).

These models will form the basis of a modular, mechanistic framework for identifying key regulators of growth-stress resilience and support experimental validation across the consortium. This position offers a unique opportunity to work at the interface of systems biology, plant science, and artificial intelligence.

The project is part of the Plant/Crop-XR program (cropxr.org/about-us/team/research), a highly collaborative 10-year national initiative involving universities and industry partners, with a mission to design resilient crops through data-driven strategies.

Key Challenges:

• Developing machine learning approaches that integrate partial biological knowledge with data-driven insights.

• Collaborating with computational modelers and experimental plant biologists to iteratively validate and refine models.

• Designing data-driven models to represent dynamic and compositional protein complexes.

• Integrating multi-omics datasets (e.g., RNA-seq, AP/MS, proximity ligation, GWAS) from various sub-projects to identify regulatory modules and interaction networks.

• Contributing to the development of hybrid models that combine mechanistic and machine learning approaches to simulate plant responses to environmental stress, and proposing "smart experiments" to iteratively improve model performance

Benefits:

• Work on cutting-edge research with real-world impact in agriculture and plant biology.

• Join a collaborative, interdisciplinary, and dynamic research environment.

• Access to state-of-the-art computational and laboratory facilities.

• Support for professional development and participation in international conferences.

To thrive as a PhD candidate, it’s crucial to have a strong research mindset driven by curiosity and passion for your topic. Reflecting on your motivation for pursuing a PhD trajectory is essential, as this path involves unique challenges and uncertainties inherent to scientific exploration. Success requires dedication, adaptability, the ability to analyze complex problems, manage your time effectively, innovate and stay resilient under pressure. Combined with the ability and willingness to work independently and collaborate well, these qualities are indispensable for a fulfilling PhD journey.

These experiences will build you as an independent researcher, expand your professional network, and pave the way for diverse career paths, inside or outside academia.

Requirements:

• A Master's degree in Computer Science, Artificial Intelligence, Computational Biology, Bioinformatics, or a related field, with an affinity for plant sciences.
• Strong background in machine learning and data analysis.
• Ability to work independently and as part of a multidisciplinary team.
• Experience with biological data integration and simulation modeling.
• Excellent programming skills (e.g., Python, R) and familiarity with machine learning libraries.
• Strong analytical thinking and problem-solving skills.
• Strong interpersonal communication and collaboration abilities
• Strong communication skills and proficiency in English.

TU Delft (Delft University of Technology) 

Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context.

At TU Delft we embrace diversity as one of our core values and we actively engage to be a university where you feel at home and can flourish. We value different perspectives and qualities. We believe this makes our work more innovative, the TU Delft community more vibrant and the world more just. Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale. That is why we invite you to apply. Your application will receive fair consideration.

Challenge. Change. Impact!

Faculty Electrical Engineering, Mathematics and Computer Science 

The Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) brings together three scientific disciplines. Combined, they reinforce each other and are the driving force behind the technology we all use in our daily lives. Technology such as the electricity grid, which our faculty is helping to make completely sustainable and future-proof. At the same time, we are developing the chips and sensors of the future, whilst also setting the foundations for the software technologies to run on this new generation of equipment – which of course includes AI. Meanwhile we are pushing the limits of applied mathematics, for example mapping out disease processes using single cell data, and using mathematics to simulate gigantic ash plumes after a volcanic eruption. In other words: there is plenty of room at the faculty for ground-breaking research. We educate innovative engineers and have excellent labs and facilities that underline our strong international position. In total, more than 1000 employees and 4,000 students work and study in this innovative environment.

Click here to go to the website of the Faculty of Electrical Engineering, Mathematics and Computer Science.

CropXR

CropXR was launched in 2023 to help make agricultural production less vulnerable to climate change and less dependent on artificial fertilizers and chemical pesticides. The institute is a joint venture of the universities of Amsterdam, Delft, Wageningen and Utrecht in partnership with Plantum, the Dutch plant breeding sector association. CropXR brings together efforts from different academic disciplines (such as plant sciences, computational and data sciences, and social sciences) and private industry to help bring about sustainable change. It receives support from NWO, the Dutch National Growth Fund, and the Foundation for Food & Agricultural Research. Learn more about CropXR at cropxr.org.

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 € 2901 per month in the first year to € 3707 in the fourth year. 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 on their website 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.  

Additional information

This PhD position is positioned within the Delft Bioinformatics Lab, part of the Computer Science department of the Delft University of Technology under supervision of Prof. Marcel Reinders, m.j.t.reinders@tudelft.nl, with close interaction of the teams at the Wageningen University Research (Prof. Ronald Pierik, Prof. Dolf Weijers, Dr. Charlotte Gommers) and Utrecht University (Dr. Lapin). More information about the molecular mechanisms work package: cropxr.org/about-us/team/research/molecular-mechanisms

Application procedure

Interested applicants should submit the following documents, no later than August 24, 2025:

• An up-to-date and detailed curriculum vitae
• Copies of relevant academic transcripts
• A cover letter, which should summarize (1) why the applicant wants the position, (2) why the project is of interest to the applicant, (3) evidence of suitability for the job, and (4) what the applicant hopes to gain from the position.
• Contact information (telephone number and email address) of at least two academic references.

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. For more details please check the Graduate Schools Admission Requirements. 

Please note:

• You can apply online. We will not process applications sent by email and/or post. 
• A pre-employment screening can be part of the selection procedure.
• For the final candidates, a knowledge security check will be part of the application procedure. For more information on this check, please consult Chapter 8 of the National Knowledge Security Guidelines. We carry out this check on the basis of legitimate interest.
• Please do not contact us for unsolicited services.