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: Interdisciplinary Dimensions of Risk in Times of Climate Change and Housing Crisis”, coordinated by Prof. Raquel Rolnik from the University of São Paulo's School of Architecture, Urbanism and Design (FAU-USP, Brazil
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-assembling macromolecular architectures with potential applications in photonic devices. Monthly stipend: R$ 12,570.00 Technical reserve: 10% of the annual fellowship amount, allocated to research-related
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. 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
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scientific and technological dissemination activities. Mandatory requirements: PhD in Materials Science and Engineering, Mechanical Engineering, Chemical Engineering, or related fields. Preference will be
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. Mandatory requirements: PhD obtained within the last seven years in a field related to the project; availability to start immediately; prior publications related to the project; proven skills in MariaDB
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original research, contributing to project management and to international academic debates on AI and technological governance. Mandatory requirements Applicants must: • Hold a PhD obtained within the last 7
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, including the use of resources such as audio description, tactile materials, and assistive technologies. Mandatory requirements: Applicants must have completed their PhD within the last seven years and be
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skills; (IV) Recommendation letter from the PhD advisor (no other letter will be accepted). This opportunity is open to candidates of any nationality. The selected candidate will receive a FAPESP Post
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Immunodeficiencies), Faculty of Medicine (FM), University of São Paulo (USP), under the supervision of Prof. Dr. Maria Notomi Sato. Requirements: PhD in Immunology or a related field. Knowledge of virology, cellular
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); - Experience with data balancing techniques; - Desirable basic knowledge of Multiple Input, Multiple Output (MIMO), Fluid Antenna System (FAS), and Compressive Sensing (CS); - PhD degree obtained within the last