77 optimization-postdoc "https:" "IMT Atlantique" Postdoctoral research jobs in Brazil
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on eligibility and benefits is available at: https://fapesp.br/en/postdoc . More information about the fellowship is at: fapesp.br/oportunidades/8978 . Where to apply Website http://www.fapesp.br/oportunidades
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(with email and/or phone). Use the subject line: “PostDoc Remote Sensing”. Applications should be sent to edson.bolfe@embrapa.br by April 30, 2026. Where to apply Website http://www.fapesp.br
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Studies), it examines the role of private companies, their relations with the public sector, and governance disputes. Activities The postdoc will map sociotechnical networks, analyze actors, and produce
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publications abd advanced English proficiency. Experience in student supervision is desirable. Candidates must also meet the eligibility criteria for FAPESP post-doctoral fellowships (see https://fapesp.br/en
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, 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
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, aiming to expand research fields. It includes the theoretical systematization of database aesthetics and the development of case studies to propose solutions that optimize metadata use. Activities involve
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), and Prof. Rubens Maciel Filho (rmaciel@unicamp.br ). The email subject line must be “PostDoc H2”. The following documents are required: - Curriculum Vitae; - Cover letter describing the motivations
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optimization, velocity modeling, seismic characterization, geological CO2 storage. Abstract: This research project aims to improve the FWI workflow in order to obtain accurate results even under limited initial
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cooperation agreement between both institutions. Position Focus: The postdoc will develop and run realistic simulations of the SWGO (Southern Wide-field Gamma-ray Observatory) detector array and help build
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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