The Institute of Mathematical and Computer Sciences at University of São Paulo (ICMC-USP) opens one post-doctoral research position in Machine Learning, and Data Mining applied to Data Streams. The selected candidate will work at ICMC-USP located in Sao Carlos/SP, Brazil.
Sao Paulo Research Foundation provides the financial support with a monthly salary of R$ 7.174,80. Financial support can also be provided to cover transportation expenses as to the move to São Carlos – Brazil. An additional grant is also provided to cover participation in highly relevant conferences and workshops, as well as research trips (limited to 15% of the annual amount of the fellowship). The position is for one year. The start date is negotiable but must occur before May 2018.
Project: Intelligent Traps and Sensors: an Innovative Approach to Control Insect Pests and Disease Vectors
Supervisor: Gustavo E. A. P. A. Batista
Job Description: The post-doc will work with Machine Learning techniques applied to Data Streams for classification and quantification. The proposed method will be applied to the task of classifying and counting insect pests and vectors captured by an automatic insect trap, among other benchmark problems. Such a trap uses a sensor that we have developed over the last years to recognize insect species using wingbeat data. The insect recognition will allow the creation of real-time insect density maps that can be used to support local interventions.
Requirements: Applicants should have Ph.D. in Computer Science or related fields with experience in Machine Learning and Data Mining. Candidates must have got their Ph.D. in the last five years.
Application: Please send your application before January 31, 2018, to email@example.com. Please indicate “post-doctoral application – Machine Learning” in the subject line. Applications should include curriculum vitae, statement of research interests and two contacts information for recommendation letters (PDF files only).
A grant from FAPESP funding agency approved as part of the e-Science research projects.