Time Series, Wavelets and High Dimensional Data: POST-DOCTORAL FELLOWSHIPS AVAILABLE

The Project FAPESP 2018/04654-9: Time Series, Wavelets and High Dimensional Data is selecting researchers interested in doing investigation in the areas below, connected to the main topics of the project.
The Fellowships are supported by FAPESP (Research Foundation of the State of São Paulo, Brazil). AREA: Statistics

• Covariance Function Estimation by Spatial Deformations
• DCS Perturbations for ARFIMA Models
• Epidemiological Vigilance - New Models and Change Detection
• Financial Time Series
• Functional Data Conglomerates
• Generalized Transformed ARMA Models
• Indirect Estimation of Time Series Models
• Minimum Variance High-Dimensioal Portfolios
• Neuroimaging
• Point Process in Functional Data
• Phylogenetic Trees and Precision Medicine
• Quasi U-Statistics
• Sazonality in High-Frequency Data
• Spatial Confounding for Generalized Linear Models
• Spatio-Temporal Deformations
• Statistical Analysis of SAR Data
• Structural Decomposition for Space-Time Models
• Volatility Estimation and Prediction for High-Dimensional Financial Data
• Wavelet Analysis in Statistics
• Wavelets in Functional and High Dimensional Data Analysis

DURATION: 24 months

Site for information:

DETAILS: Full details can be found at and links therein.

MONTHLY PAYMENTS: R$ 7,373.10 (tax-free)

OTHER BENEFITS: Tickets (round-trip) and R$ 7.373,10 (see rules at
We seek doctors in Statistics (or related areas) with strong research potential that can develop supervised work on the aforementioned topics. It is desirable that the candidates have proven experience in data analysis and computer skills. The selected researchers will work in São Paulo or Campinas under the supervision of one the project’s principal investigators.

Interested candidates should apply to The application email should contain the following:
(i) A letter (pdf file) explaining the candidate’s background, in which topic(s) they’d like to work and the reasons why they feel they are suitable for the proposed task.
(ii) Candidate’s CV (pdf file).
(iii) PhD dissertation summary (pdf file) and a two-page summary of published works (pdf file).
(iv) E-mail and postal (official university or professional) addresses for two former research supervisors or course professors which are willing to write recommendation letters.

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