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Terrestrial Ecosystem Science & Technology (TEST)

Current Open Position(s)

Summer Undergraduate Internship
Investigating plant growth using physiology and remote sensing

We need to increase food production by 70% by the year 2050 to meet global food demand. Increasing crop yield is a key goal for ensuring food security but this must be accomplished in a changing climate where elevating yield will become more challenging. In order to improve yield we must first understand the factors limiting growth in plants, and the ways in which plants respond to different environmental conditions. The use of high-throughput techniques such as remote sensing to monitor plant traits non-destructively throughout their life cycle is a valuable way in which plant breeders can increase the speed of crop breeding. Join BNL scientists for a plant science research project in the glasshouse, where you will be measuring plant traits and linking them to leaf spectra to enable remote sensing approaches that can be used to accelerate physiological breeding. You will also have the opportunity to collect data using physiological and biochemical techniques, measure leaf spectra and build models to predict those traits from leaf optical properties. You will be welcomed into a productive and supportive team environment – learn more about our friendly group at

Supervisor Dr. Angela Burnett

For more information about the Department of Energy ‘Science Undergraduate Laboratory Internships’ (SULI) program, and to apply, visit

Summer Undergraduate Internship
Investigating tropical leaf phenology: from individual crowns to landscapes

Tropical phenology is critical to understanding and modelling how climate variation influences tropical forest ecosystem function and differentially affects tropical plant species, but remains poorly understood. Here, we propose a research project, aiming to improve our understanding of leaf phenology patterns in the tropics from individual crowns up to the entire landscapes. We will use the recent tower-mounted camera image timeseries collected at three Panamanian tropical evergreen forests. The project will include four components: (i) segregate each individual tree crown within the camera image, (ii) develop algorithms to automatically extract leaf phenology information for each individual crown from the camera image time series, (iii) conduct landscape statistics to estimate community-average leaf phenology patterns for different canopy growth environments (e.g. canopy trees vs. understory trees) and across tropical forests spanning in large rainfall gradients, and (iv) connect camera-extracted leaf phenology to evaluate satellite detected vegetation phenology at the same sites. The completion of this work will significantly advance our understanding of leaf phenology patterns in the tropics, and generate a great dataset for future more explicit exploration of the mechanistic linkages among climate, plant species and phenology in the tropics.

Supervisor: Dr. Jin Wu

For more information about the Department of Energy ‘Science Undergraduate Laboratory Internships’ (SULI) program, and to apply, visit 

Research Collaborator: Open Source Software Developer

We are looking for a University undergraduate or postgraduate student with an interest in using their skills to help us with software development. The Open Source Developer will be responsible for assisting in a number of activities including the design and development of command-line tools, web, and database applications for scientific and ecological research. For example, tasks might include development of automated scientific data processing workflows and analysis. The research collaborator would be eligible for a $71 per day stipend and would have the opportunity to work in a collaborative research environment with scientists in the TEST group who are working on a range of projects including research in the Arctic and tropics, and the use of Unmanned Aerial Systems for ecological research.

Essential duties and required skills

  • Documenting code with Doxygen or similar
  • Experience with python
  • Code version control through GitHub or similar collaborative coding environments

Desirable skills

  • Background in biological sciences
  • Experience with R, C/C++, Fortran

There is no set start and end point for the position and we can be flexible to accommodate your schedule but we are looking to identify a suitable person shortly. To be considered for this opportunity please send your CV to Dr. Alistair Rogers, or Dr. Shawn Serbin,