Sort by
Refine Your Search
-
students through informal mentoring, reading groups, or supervision-related activities, under the coordination of the faculty supervisor; - Submit a formal annual scientific report describing their progress
-
; - Interact with graduate students through informal mentoring, reading groups, or supervision-related activities, under the coordination of the faculty supervisor; - Submit a formal annual scientific report
-
related to the use of LiDAR data in forest applications, as well as experience with deep learning methods, will be considered an advantage. How to apply: Send CV, statement of interest, and the names of two
-
Bacteriophages) at the University of São Paulo (USP) invites applications for a FAPESP-funded post-doctoral position to develop bacteriophage bioinformatics methods and to apply these and other methods
-
; - Experience with data processing techniques. Desirable knowledge of methods such as Neighborhood Components Analysis (NCA), Locally Linear Embedding (LLE), and t-distributed Stochastic Neighbor Embedding (t-SNE
-
diseases (CDV), and diabetes. Methods: The ELSA-Brasil is a prospective multicentric cohort study that recruited civil servants aged 35-74 living in 6 metropolitan areas in Brazil. The study began in 2008
-
in engineering or a field related to the project; • Knowledge and proven expertise in computational optimization methods and discrete-event simulation, with experience in regular service design
-
control associated with the crop. Disease management methods include plant breeding through conventional genetic improvement or marker-assisted selection, in addition to other approaches commonly applied in
-
Foundation (FAPESP), and combines statistical analysis, spatial methods, and qualitative research. Georeferenced data from the Military Police and the Municipal Secretariat of Urban Security will be used
-
Research Foundation (FAPESP). Requirements: • Completed PhD in any field; • Experience in comparative public policy analysis; • Experience with qualitative and quantitative methods; • Intermediate knowledge