Looking to list your PhD opportunities? Log in here.
This project is no longer listed on FindAPhD.com and may not be available.
Click here to search FindAPhD.com for PhD studentship opportunitiesAbout the Project
The project is a BBSRC CASE PhD Studentship with King's College London, conducted in collaboration with Rothamsted Research and Bayer CropScience AG. The project will be jointly supervised by Prof. Martin Wooster (KCL), Dr Malcolm Hawkesford (Rothamsted) and Dr Juan Pedro Ruiz-Santaella (Bayer CropScience AG).
At King's College London the student will be a member of the Earth and Environmental Dynamics (EED) Research Group of the Department of Geography. Training on research methods, remote sensing, GIS, and environmental monitoring & modelling will be available, and they will attend appropriate national and European scientific meetings, for example the annual "Workshop on UAV-based Remote Sensing Methods for Monitoring Vegetation". Training in software development will be given as required.
At Rothamsted the student will be part of a multi-disciplinary team involved in optimising crop perfomance (gene regulation, plant physiology, genetics and crop trials). The student will be given training in the trials design and ground-based phenotyping technologies used to compare against the UAV-based methods. Rothamsted provides a range of taught courses, e.g. in Crop Protection, to which the student will have full access as required, and access will also be provided to the seminars, workshops, and open weekends covering relevant areas of biotech/agricultural sciences.
Whilst at the Bayer CropScience field station the student will be part of an interdisciplinary working team of biologists, agronomists, breeders as well as field technicians, and their work will be supervised by an experienced agronomist on farm and by a senior scientist at the headquarters in Monheim (Germany).
The project will utilise a mix of airborne remote sensing, UAVs, photogrammetry, algorithm development (computer coding in Python, IDL, or R), laboratory instrument testing, use of scene and spectral simulation models, and substantial fieldwork in the UK and later overseas. Applicants should have a 1st or 2:1 degree in a science, engineering or geographic discipline, ideally an additional relevant MSc qualification or be currently on an MSc degree, and some experience relevant to at least one of the above areas. A driving license would be useful.
The project can commence any time between 1st January and 30 September 2015, and graduates with an existing good quality MSc degree, and those currently on MSc courses, are encouraged to apply.
Application deadline is 1st December 2014. Please send your CV and cover letter via email to [Email Address Removed]
Please check that you meet BBSRC requirements for both academic qualifications and UK residential eligibility before applying: http://www.bbsrc.ac.uk/web/FILES/Guidelines/studentship_eligibility.pdf.
Funding Notes
References
• Huang, Y., Thomson, S. J., Hoffmann, W. C., Lan, Y., & Fritz, B. K. (2013). Development and prospect of unmanned aerial vehicle technologies for agricultural production management. International Journal of Agricultural & Biological Engineering, 6(3).
• Sepulcre-Cantó, G., Pablo J. Zarco-Tejada, J. A. Sobrino, José AJ Berni, J. C. Jiménez-Muñoz, and Jean-Philippe Gastellu-Etchegorry (2009) Discriminating irrigated and rainfed olive orchards with thermal ASTER imagery and DART 3D simulation, Agricultural and Forest Meteorology, 149, 962-975.
• White, J. W., Andrade-Sanchez, P., Gore, M. A., Bronson, K. F., et al. (2012). Field-based phenomics for plant genetics research. Field Crops Research, 133, 101-112.
• Hawkesford MJ (2013) Reducing the reliance on nitrogen fertiliser for wheat production, Journal of Cereal Science, http://dx.doi.org/10.1016/j.jcs.2013.12.001.
• Pedro Andrade-Sanchez, Michael A. Gore, John T. Heun, Kelly R. Thorp, A. Elizabete Carmo-Silva, Andrew N. French, Michael E. Salvucci, Jeffrey W. White (2013) Development and evaluation of a field-based high-throughput phenotyping platform. Functional Plant Biology, 41, 68 - 79.
• http://libcatalog.cimmyt.org/download/cim/96140.pdf
• http://libcatalog.cimmyt.org/download/cim/96144.pdf