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<td>[Ieee_vis_open_positions] Postdoctoral Position in
Computer Vision Analysis of Growing Plants</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">Date: </th>
<td>Wed, 20 Feb 2013 15:58:11 -0800</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">From: </th>
<td>Nelson Max <a class="moz-txt-link-rfc2396E" href="mailto:max@cs.ucdavis.edu"><max@cs.ucdavis.edu></a></td>
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<td><a class="moz-txt-link-abbreviated" href="mailto:max@cs.ucdavis.edu">max@cs.ucdavis.edu</a></td>
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<td>UCDavis</td>
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<th valign="BASELINE" nowrap="nowrap" align="RIGHT">To: </th>
<td><a class="moz-txt-link-abbreviated" href="mailto:ieee_vis_open_positions@listserv.uni-tuebingen.de">ieee_vis_open_positions@listserv.uni-tuebingen.de</a></td>
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<pre>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 <a class="moz-txt-link-rfc2396E" href="mailto:max@cs.ucdavis.edu"><max@cs.ucdavis.edu></a>.
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."
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