Call for Applications: PhD Positions on Plant Phenotyping with Imaging and Sensors
Purdue University’s Department of Agricultural and Biological Engineering has been ranked as the #1 Graduate Program by US News & World Report for the past 7 consecutive years. The program calls for applications for PhD positions working on imaging and sensors development for plant phenotyping, which are available in Spring/Summer/Fall of 2016. The successful candidates will be involved in the development of next generation plant phenotyping systems. More specifically, the research will include integrating modern sensor technologies such as hyperspectral, 3D, thermal, fluorescent cameras, and so on for plant screening purpose. The candidates will also be studying imaging processing and machine vision algorithms. Statistical modeling and big data analysis will be conducted to assist the search of plant genes in a much faster speed than before, so as to produce more and safer food for the world’s growing population.
The candidate is expected to have a bachelor or master’s degree in Agricultural Engineering, Computer Science, Computer Engineering, Electrical Engineering, Mechanical Engineering or other related areas. Computer programming at science level at minimum is required. Research experience and skills in image processing, machine vision, photography, robotics, automation and control, mobile apps development, CAD design, statistics modeling, artificial intelligence algorithms, circuit designing are highly desired though not required.
We are always looking for outstanding students to join our innovative research program.
Outstanding students who apply early may be considered for prestigious fellowships.
Program starting time: Spring, Summer and Fall 2016.
We encourage you to submit your application or contact us as early as possible.
Be sure to include:
Check our website for further details.
https://engineering.purdue.edu/ABE/InfoFor/ProspectiveGraduateStudents
Please feel free to contact Dr. Jian Jin (jinjian@purdue.edu) with questions.