Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
academic experience will be requested to finalize the process and grant the fellowship. Failure to present these documents when requested will result in elimination from the selection process. 2 Candidate
-
28 Feb 2026 Job Information Organisation/Company FAPESP - São Paulo Research Foundation Research Field Engineering Researcher Profile Established Researcher (R3) Application Deadline 15 Mar 2026 - 23:59 (UTC) Country Brazil Type of Contract To be defined Job Status Not Applicable Is the job...
-
position within a Research Infrastructure? No Offer Description Activities: This research investigates the use of artificial intelligence in developing data visualization systems for born-digital collections
-
position within a Research Infrastructure? No Offer Description Activities: The post-doctoral fellow will be responsible for: i) Acquisition, processing, and digital classification of satellite and drone
-
well as digital twins, with a focus on urban resilience and energy security, integrating real infrastructure data from the city of Santo André. Fellowship Topic: Digital Twin to Support the Continuity of Urban
-
international journals (IEEE Transactions on Wireless Communications, Transactions on Signal Processing, etc.). The post-doctoral researcher should be qualified to apply for professorships and endorse positions
-
, assembly, adaptation, operation, and optimization of plasma systems and reactors; on the processing of liquid materials and precursor suspensions; on the treatment and processing of materials by thermal
-
Foundation (FAPESP) and hosted by University of São Paulo's São Carlos School of Engineering (EESC-USP) in Brazil. The project concerns the investigation of surface dryout near the critical point during flow
-
Resources into Bioproducts and Bioenergy.” Required Expertise The candidate must demonstrate proven experience in: - Renewable hydrogen production; - Proficiency in thermochemical modeling and process
-
involve developing an approach that uses Knowledge Organization (KO) metadata and ontologies to optimize parallel processing and scheduling policies (via Kubernetes) for Machine Learning tasks. The fellow