Enhancing plant resilience through biologically-inspired machine learning Delft University of Technology Delft Bioinformatics Lab Netherlands ZH Delft www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17879<https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17879> Description We are seeking a highly motivated PhD candidate to join our research team focused on enhancing plant resilience using cutting-edge data analysis and machine learning techniques. This exciting opportunity will involve designing and integrating biological knowledge into machine learning models to uncover mechanisms controlling plant resilience. The ultimate goal is to connect these findings with simulation models to predict how plants respond to environmental stresses such as drought and extreme temperatures, supporting plant breeding industry to develop crops that can withstand combinations of stresses brought by a changing climate. The project is part of the Crop-XR program, a highly collaborative 10-year national initiative of universities and industry, with a mission to grow resilient crops developed by a data-driven design. Key Challenges: - Develop and implement biologically-inspired machine learning algorithms aimed at identifying gene regulatory networks that influence plant resilience. - Integrate spatial and temporal data to establish connections between gene modules and specific plant organs and developmental stages. - Utilize predictive modeling to identify key genes with significant impacts on stress resilience, thereby pinpointing potential targets for the breeding of more resilient plant varieties. - Collaborate closely with modelers and plant biology experimenters to validate and enhance computational models, ensuring their accuracy and applicability. - Contribute to the integration of mechanistic and machine learning models to simulate how plants respond to environmental changes and leverage these simulations to propose new experiments that generate "smart data" for ongoing model refinement and improvement. Benefits: - Opportunity to work on cutting-edge research with significant real-world impact. - Collaborative and dynamic research environment. - Access to state-of-the-art facilities and resources. - Support for professional development and attendance at international conferences. 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. The PhD will be done in close collaboration with the Bioinformatics Group at Wageningen University, and co-supervised by Prof. Dick de Ridder. ________________________________ Qualifications - A Master's degree in Computer science, Artificial Intelligence (AI), Computational Biology, Bioinformatics, or a related field with an affinity to plant sciences. - Strong background in machine learning and data analysis. - Experience with biological data integration and simulation modeling. - Excellent programming skills (e.g., Python, R) and familiarity with machine learning libraries. - Strong analytical and problem-solving skills. - Ability to work independently and as part of a multidisciplinary team. - Strong interpersonal communication and collaboration abilities - Good communication skills and proficiency in English. 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. ________________________________ Start date As soon as possible ________________________________ How to Apply Please use the online application form on the vacancy website: www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17879<https://www.tudelft.nl/over-tu-delft/werken-bij-tu-delft/vacatures/details?jobId=17879> ________________________________ Contact Marcel Reinders m.j.t.reinders@tudelft.nl<https://careers.iscb.org/jobs/view/%3ca%20%20href=%22mailto:m.j.t.reinders@tudelft.nl%22%3em.j.t.reinders@tudelft.nl%3c/a%3e>