85 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "Mines Paris PSL" positions in Brazil
Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
-
Field
-
http://www.fapesp.br/oportunidades/9131 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility of fellows: country/ies of residence: All
-
in Amazonia and background on meteorology, chemistry, biology and environmental physics is desirable. For more details access the link with the full proposal: https://1drv.ms/b/c/87b35e20128a7567
-
Science, Computer Engineering, or a related field, completed before the fellowship start date. Candidates should demonstrate experience in at least two of the following areas: compilers, parallel programming
-
http://www.fapesp.br/oportunidades/9137 Requirements Additional Information Eligibility criteria Eligible destination country/ies for fellows: Brazil Eligibility of fellows: country/ies of residence: All
-
and Supply (SAASP). Duration: 36 months (full-time) Expected start: April 2026 (flexible) How to apply Applications should be submitted only through the Google Form: https://docs.google.com/forms/d/e
-
). Full-time dedication required. Application: send motivation letter and CV. More informastion about the fellowship is at: fapesp.br/oportunidades/9140 . Where to apply Website http://www.fapesp.br
-
, 2026, with the email subject “Opportunity PDP4-2026.” Website for additional job details https://cepenfito.org.br/ Work Location(s) Number of offers available1Company/InstituteEngineering Research Center
-
learning-based segmentation, multimodal image fusion, and radiomic feature extraction to construct clinically relevant prognostic models. Conducted at the Heart Institute (InCor) of Hospital das Clínicas
-
. Requirements: PhD completed less than 7 years ago in Computer Science or related areas; experience in machine learning and data science (supervised/unsupervised models, recommendation and evaluation/robustness
-
Python and R; - Demonstrable experience with Machine Learning; - Excellent problem-solving skills and the ability to work both independently and as part of a team. This position is for full-time, on-site