PhD Position at TU Delft: Mathematical Data Analysis For Agriculture
This PhD position is a part of the project “Flight to Vitality”, which is jointly financed by the European Union (Rural Development Programme) and Dutch industry (HZPC and Averis Seeds). The project aims at developing a method for testing and characterizing the vitality (vigor) of potato seeds, so that different potato varieties can be optimally supplied to various customers all over the world. Vast amounts of physical, chemical, microbiological, and genomic data will be collected during this project and TU Delft is charged with extracting useful phenotypic information from these data and meaningfully reducing the size of data sets.
The PhD project focuses on the mathematical processing of data and will involve a combination of data-extraction, modelling, and order-reduction techniques. Initial priority will be given to a unique set of visual and multi-spectral timelapse images collected by cameras in climate-controlled rooms and in field trials at various locations in the world. The goal is to efficiently extract the maximum amount of useful phenotypic information from the images about the early stages of the plant development, such as the time of emergence, number of sprouts, leaf area, plant height, etc. The second priority is to develop efficient and meaningful order-reduction techniques for physical, chemical, microbiological, and genomic data about the seed potatoes. PhD student is expected to work in a multidisciplinary environment and should be able to communicate with project colleagues and partners from different educational and cultural backgrounds. This PhD project provides an excellent opportunity to become a professional applied mathematician skilled at practical implementation of mathematical ideas in an industrial/agricultural environment.
MSc in Applied Mathematics, Applied Physics, Electrical Engineering, Computer Science or a related field. For non-mathematical MSc’s – familiarity with numerical analysis and applied linear algebra as demonstrated by courses and/or projects. An applicant should have a strong interest in real-world problems, numerical methods, data processing, and applied linear algebra, as well as programming and communication skills.
When and how to apply
Position is open for applications from February 1, 2019 and will be filled in March 2019. To apply: send your CV, contact details of two referees, transcript of university grades per subject, copy of your Master Thesis, and a letter of motivation to the following addresses:
Neil Budko (firstname.lastname@example.org)
Kees Vuik (email@example.com)
Feel free to contact us for additional information about the PhD position and the Project.