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Paulo state, Brazil, in the area of compilers, runtimes, and High-Performance Computing, focusing on the convergence of HPC and Artificial Intelligence. The project will develop runtime optimizations and
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on performance. Selection Process and Application: Candidates must submit their application materials to mcfjr@unicamp.br by April 05, 2026, using “PD Fellowship Application” as the subject line. The required
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clinical decision-support axis, focusing on building robust and generalizable models, incorporating explainability techniques, performing rigorous quantitative validation using clinically meaningful metrics
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layouts; quantify performance (energy/angular resolution, trigger efficiency, background rejection, sensitivity, trade-offs); Define a SWGO–CTAO synergy roadmap for key programs: transients, diffuse
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-month period, depending on the fellow's performance. According to current regulations, fellows may be replaced even before 12 months if they withdraw or their performance is incompatible with what
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projects with tangible outputs; programming skills; operation and planning of electric power distribution networks; and database management. Recently graduated PhD holders are preferred. Application Process
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, Brazil – to conduct a project qhose objective is to evaluate the carbon stock and silvicultural performance of 25 species of Eucalyptus monitored for over three decades across a broad edaphoclimatic
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innovative approaches to reduce signaling load on networks. Furthermore, the researcher is expected to develop mathematical models and tools to rigorously analyze the performance of such algorithms. Extensive
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for an additional 12 months (totaling 24 months), contingent upon performance and results. Stipend: R$ 12,570.00 per month (tax-free). Location: In-person at LABECMar/Unifesp, Santos, São Paulo state, Brazil. Start
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framework for analyzing and comparing the results of the field experiment with the CAETÊ model outputs; perform a first-order upscaling of the initial results of the AmazonFACE field experiment to the entire