Monsanto Graduate Student Scholarship

It is with great excitement to announce that Monsanto has launched a graduate scholarship for diverse students in the STEM field. The Monsanto Graduate Scholarship is part our company’s broader focus on innovation and investment in agriculture. To meet the challenges the world faces in feeding nine billion people by 2050, investing in future leaders pursuing STEM careers in food and agriculture is key. The next generation of innovators will be the ones to ascend and meet the challenges of global food security.  We will award ten $25,000 scholarships to graduate students in the STEM fields.

The scholarship application is online now. Interested students may apply online. The link to the application is below.

http://www.monsanto.com/careers/pages/student-scholarships.aspx

Timeline
·         The deadline to apply is June 1st, 2015.
·         Winners will be announced by July 1st, 2015.
·         Payments made by August 1st, 2015

Requirements
·         Must be a diverse student enrolled in a Master’s program in a STEM related field
(all minorities and women will be considered)
·         3.0 GPA
·         PhD candidates will not be considered

Program
·         Awarding (10) $25,000 scholarships
·         Open to all Universities
·         Diverse Students Studying STEM
·         All minority and female candidates will be considered

Submit Abstracts by May 17 for the NIST Bioimage Informatics Conference

NIST is hosting the ‪‎Bioimage Informatics conference on Oct. 14-16, 2015, in Gaithersburg, Md. The conference will bring together researchers and practitioners in the field of image informatics for the life sciences. The BioImage Informatics (BII) conference was created in 2005 to establish a unique communication network among the scientists working in the field of BioImage Informatics.

Please visit the NIST website for submission process and guidelines. Abstract deadline is May 17, 2015.

NSF EPSCoR Eligibility in Missouri

NSF EPSCoR has released the new FY15 EPSCoR eligibility table.  The link to it can be found here.  A jurisdiction is eligible to participate in the NSF EPSCoR Research Infrastructure Improvement Grant Program (RII) if its most recent 3-year level of NSF Research Support is equal to or less than 0.75% of the total NSF Research and Related Activities (R&RA) budget.

Missouri’s percentage on NSF Research and Related Activities (R&RA) is 0.78. Currently participating EPSCoR jurisdictions that exceed the 0.75% of R&RA eligibility threshold in a given fiscal year may not compete in new Research Infrastructure Improvement (RII) competitions. However,  jurisdictions remain eligible for Co-Funding and Outreach & Workshop support for a subsequent three (3) years.

EPSCoR Reporting Deadlines

The following links are only for current participants in the Missouri Transect or Plant Imaging Consortium.

The deadline for Missouri Transect participants to submit their reporting to Drupal is April 1.  The deadline for Missouri PIC participants is April 3.  Please follow the link for both reporting pages: https://epscorreporting.missouri.edu/

Or click on your project logo below:

missouri_transect_largePIC Logo

RFP for Dynamics of Coupled Natural and Human Systems (CNH)

The Dynamics of Coupled Natural and Human Systems (CNH) Program supports interdisciplinary research that examines human and natural system processes and the complex interactions among human and natural systems at diverse scales.  Research projects to be supported by CNH must include analyses of four different components:  (1) the dynamics of a natural system; (2) the dynamics of a human system; (3) the processes through which the natural system affects the human system; and (4) the processes through which the human system affects the natural system.  CNH also supports research coordination networks (CNH-RCNs) designed to facilitate activities that promote future research by broad research communities that will include all four components necessary for CNH funding.

PROPOSAL SOLICITATION

http://www.nsf.gov/pubs/2014/nsf14601/nsf14601.htm

DUE DATES

Full Proposal Deadline Date:  November 17, 2015

Third Tuesday in November, Annually Thereafter

All CNH proposals must be submitted by 5:00 PM (local time of submitting organization) on the annual CNH proposal-submission deadline, which is the third Tuesday of November.

EDUCATIONAL OPPORTUNITY

This program provides educational opportunities for  Undergraduate Students, Graduate Students, K-12 Educators . Individuals interested in applying for funding should see the program guidelines above.

Citizen Science 2015

Sandra Arango-Caro attended the inaugural conference of the Citizen Science Association (CSA), Citizen Science 2015.  She presented a poster on the Missouri Transect citizen science project, Missourians Doing Impact Research Together (MO DIRT), headed at the Danforth Center in St. Louis.  MO DIRT was the only project presented at the conference that focused on citizen-led measurements of soil health, signifying an important research gap that MO DIRT will fill.  You can read about her experience here.

Sandra Arango-Caro presenting on MO DIRT

Sandra Arango-Caro presenting on MO DIRT

Call for Papers

Machine Vision and Applications
Special Issue on Computer Vision and Image Analysis in Plant Phenotyping

Website: http://www.plant-phenotyping.org/CVPPP2014-Special-Issue/

Important Dates

Submission:         April 20 2015
First decisions:    June 20 2015
Revision deadline:  July 30 2015
Final decisions:    Aug 30 2015
Online publication: November 2015

Scope

Plant phenotyping is the identification of effects on the phenotype (i.e., the plant appearance and behavior) as a result of genotype differences (i.e., differences in the genetic code) and the environment. Previously, the process of taking phenotypic measurements has been manual, costly, and time consuming.  In recent years, non-invasive, imaging‐based methods have become more common. These images are recorded by a range of capture devices from small embedded camera systems to multi-million Euro smart-greenhouses, at scales ranging from microscopic images of cells, to entire fields captured by UAVs.

These images need to be analyzed in a high throughput, robust, and accurate manner. UN-FAO statistics show that according to current population predictions we will need to achieve a 70% increase in food productivity by 2050, simply to maintain current global nutrition levels. Phenomics -large-scale measurement of plant traits– is the bottleneck here, and machine vision is ideally placed to help. However, the occurring problems differ from usual tasks addressed by the computer vision community due to the requirements posed by this application scenario.
Dealing with these new problems has spawned new specialized workshops such as CVPPP (Computer Vision Problems in Plant Phenotyping) which was held for the first time in conjunction with ECCV 2014, and the stand-alone workshop IAMPS (Image Analysis Methods for the Plant Sciences) now in its fourth year.

The overriding goal of this special issue is to focus on submissions that propose interesting computer vision solutions, but also submissions that introduce challenging computer vision problems in plant phenotyping accompanied with benchmark datasets and suitable performance evaluation methods.

Specific topics of interest include, but are not limited to, the following:

  • problem statements accompanied by image data sets defining plant phenotyping challenges, complete with annotations if appropriate, and accompanied with benchmark methods wherever possible, and suitable evaluation methods
  • advances in segmentation, tracking, detection, reconstruction and identification methods that address unsolved plant phenotyping scenarios
  • open source implementation, comparison and discussion of existing methods

Submission

Authors are encouraged to submit original work that has not appeared in, nor is in consideration by, other journals. Previously published conference papers can be submitted in extended form (with additional supporting experiments and a more detailed technical description of the method). All papers will be subject to expert peer review.

Further information on the process (as well any special issue related updates) are available at: http://www.plant-phenotyping.org/CVPPP2014-Special-Issue/

The electronic copy of a complete manuscript (10-15 pages in the Machine Vision and Applications publication format) should be submitted through the journal manuscript tracking system at the web site: http://www.editorialmanager.com/mvap/ indicating that the contribution is for the special issue “Computer Vision and Image Analysis in Plant Phenotyping”.

Guest editors (alphabetical order)

Hannah Dee, Aberystwyth University, UK (hmd1@aber.ac.uk)
Andrew French, University of Nottingham, UK (Andrew.P.French@nottingham.ac.uk)
Hanno Scharr, Forschungszentrum Jülich, Germany (h.scharr@fz-juelich.de)
Sotirios Tsaftaris, IMT Lucca, Italy (s.tsaftaris@imtlucca.it)