Postdoctoral Position in Computer Vision Analysis of Growing Plants at U. C. Davis, California, USA

Postdoctoral Position in Computer Vision Analysis of Growing Plants at U. C. Davis, California, USA

We have a Postdoctoral scholar position in the Department of Computer 

Science at the University of California, Davis CA, USA, for a researcher in 

computer vision, image processing, image segmentation, or shape matching, 

to work on a project to understand the growth of tomato plants. The work 

includes multi-view stereo reconstruction, registration and joint 

analysis of multi-view stereo, thermal, and "pushbroom" multispectral 

imagery of growing plants, feature tracking in Micro Computed Tomography 

images of growing plant meristems, and developing models of plant 

growth, as well as helping to mentor two graduate students doing this 

research. The position is for 12 months, with a possible extension for 

up to 3 more months, and could start anytime in the calendar year 2013. 

Appointment as a postdoctoral scholar requires a doctoral degree (Ph.D., 

M.D.) or foreign equivalent (in this case, in Computer Science or a 

related filed such as Electrical Engineering or Mathematics). To apply, 

e-mail a CV to Nelson Max . The abstract of our 

funded project is included below.

"In the near future, population increases combined with climate change 

are expected to place unprecedented demands on agriculture. Droughts are 

predicted to become more prevalent, nitrogen and phosphorous will become 

limiting, and saline environments may be accessed as arable land becomes 

depleted. Developing crop varieties to cope with such stresses under 

unpredictable climate conditions will require a nuanced understanding of 

genetic responses to environmental changes. Additionally, valuable water 

and fertilizer must be efficiently triaged to those plants facing the 

greatest deficit of resources. In this project, we will study responses 

to drought, salinity, and nitrogen and phosphorous deprivation in 

tomato, the second most valuable vegetable crop in California and 

worldwide. We will use RNA expression profiling to identify those genes 

most responsive to environmental stresses not only in domesticated 

tomato, but also its wild relatives, which may harbor sensitized 

responses to environmental change. We will develop high throughput 

methods to measure biochemical markers of stress, including remote 

multi-spectral sensing, thermal imaging, and stereo reconstruction. 

Additionally, we will analyze changes in the development and morphology 

of organs using Micro Computed Tomography to image the meristem and 

observe changes in leaves from their inception. We will direct our 

understanding of stress response towards the creation of genetically 

engineered tomato varieties that, from the outset of specific stresses, 

will visibly express a reporter, changing the color or structure of the 

plant. Such sentinel plants will allow the application of water and 

fertilizer as needed, rather than broadcasting these resources on 

potentially wasteful schedules."