• Description:

    Join the top-tier university TU Delft in a collaborative effort with CropXR to develop intelligent methods for breeding resilient crops. This project aims to employ control theory and machine learning to study natural systems’ robustness, leading to the creation of sustainable and climate-adaptive crops. As a PhD candidate, you will work on developing novel systems biology methods, combining dynamical models analysis, and machine learning techniques, contributing to advancements in agricultural science.

    As a PhD candidate, you will be part of the collaborative effort between TU Delft and CropXR, focusing on developing intelligent methods for breeding resilient crops. You will work on developing novel systems biology methods, employing control theory and machine learning techniques to analyze large datasets from plant biology. The project aims to accelerate breeding for complex resilience traits in various crops, contributing to sustainable agriculture and climate change mitigation.

    Qualifications 

    • MSc degree in systems and control, applied mathematics, electrical engineering, computer science, or related fields
    • Basic knowledge of control theory and/or machine learning
    • Strong analytical skills and ability to work across research domains
    • Basic programming skills, preferably in Python
    • Proficiency in English language (B1 level and above)

    How to Apply

    Interested candidates should apply online via the application button before May 15, 2024. The application must include a 1-page motivation letter, CV, academic transcripts of both BSc and MSc degrees, a part of the MSc thesis, and a scientific report or paper demonstrating writing skills. Highlight relevant competencies and achievements in the motivation letter and/or CV. For inquiries about the application procedure, contact the HR advisor at recruitment-me@tudelft.nl.

     

  • Fields

    • Computer Science

    • Engineering

    • Mathematics

  • Qualifications

    • Master

  • Share Position