Phd Position Enhancing Plant Resilience Through
2 weken geleden
PhD Position Enhancing Plant Resilience through Biologically-Inspired Machine Learning-
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
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.
**Requirements**:
- 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.
Conditions of employment
The TU Delft offers a customisable compensation package, discounts on health insurance, and a monthly work costs contribution. Flexible work schedules can be arranged.
For international applicants, TU Delft has the Coming to Delft Service. This service provides information for new international employees to help you prepare the relocation and to settle in the Netherlands. The Coming to Delft Service offers a Dual Career Programme for partners and they organise events to expand your (social) network.
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.
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
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