Postdoctoral fellowship in Artificial Intelligence-based flood forecasting (Sao Paulo, Brazil)

The research applies machine learning techniques to predict floods using data from sensors deployed in São Carlos - SP. Candidates for this position must have obtained their Ph.D. in CS (or related fields) in the last 5 years. Other requirements are to have authored articles in the area and to demonstrate experience in research and software development, particularly in Python. The selection criteria will include demonstrated research capacity in the call field, a solid background in machine learning, and English speech and writing skills. It is also desirable that the candidate knows how to work in groups and can interact with researchers from other areas, such as hydrology. To apply, send the following items by email to Professor Jó Ueyama by 01/31/2023. Professor Ueyama's email address is joueyama@icmc.usp.br. Please send the pdf files of the following documents: 1. Letter of interest containing complete information of contact, year of graduation, and citizenship/immigration status, clearly addressing the research above; 2. Resume; 3. Cover letter including names and contact information for three references. Enter "Postdoc – Flood Prediction" in the message's subject field.

The accepted candidate will do research at the Institute of Mathematics and Computer Science of the University of Sao Paulo (at the São Carlos campus, which is 180 miles from Sao Paulo city www.icmc.usp.br). The grant is for one year and can be renewed upon the candidate's performance.

 

 

The post-doctoral fellowship includes a monthly stipend of R$8,479.20 (about USD 1,600 net pay) and research contingency funds (10% of the annual value of the fellowship each year). São Carlos is a university town with a low living cost. The rent for a one-bedroom apartment costs less than USD 300. Also, two universities in town provide a high degree of education and culture for São Carlos. For more details, check out Fapesp's webpage http://www.fapesp.br/