Computer vision and application aware compression for phenotyping

1 Research Collaborator position
(Deadline June 25th, 2014 12:00 )
Fields
Image and video compression, image analysis, pattern recognition, machine learning, data mining, embedded systems
Activity
We have funding from the EU to investigate affordable imaging sensors and distributed analysis frameworks for plant phenotyping. Our proposed framework involves the development of imaging sensors based on low cost ARM devices as well as software solutions that employ image and video compression (and particularly application aware compression) to minimize the necessary bandwidth. We are looking for an enthusiastic and strongly motivated junior researcher to join our lab in Italy and propose innovative approaches to the above problems. The research collaborator is expected to focus mostly on research.
Formal requirements
 Possession of a 4 or 5-year degree or equivalent MSc’s level education in Computer Science, Information Engineering, or Electrical Engineering. An excellent level of both written and spoken English is mandatory.
Specific requirements
Candidates should be near the completion of a Ph.D. in the intersection of image and video compression with computer vision and machine learning. A good record of international publications demonstrating prior experience is required. Experience with embedded devices, application aware compression, and distributed computing on the cloud, are considered a plus. Experience in image based plant phenotyping problems is considered a plus. The candidate should have good programming skills and a good mathematical background.
Gross amount
€ 20.000,00 a year
Duration
1 year not renewable
Job Research Area: 
CSA
Job Research Unit: 
PRIAn
Job Contract Type: 
Assegno di ricerca
Full call
First meeting of the Selection Committee
June 25th, 2014
Preliminary shortlist
Preliminary shortlist
Second meeting of the Selection Committee
July 1st, 2014 from 14.00 - Piazza San Francesco, 19 Lucca
Final ranking
Final ranking

Application

Apply ONLINE only.
Before starting prepare the application attachments and information as listed below.

Info

  • Personal info and contact info (compulsory)
  • Number of your Identity Document (Passport or Identity Card) (compulsory)
  • University degree and ongoing PhD (compulsory)

Attachments

  • Your CV in English (compulsory)