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for this position must have a PhD in Computer Science/Engineering or Electrical Engineering, a good background in Digital Design and Computer Architecture, and strong programming skills in Hardware Description
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: Develop computer vision algorithms to analyze public datasets (e.g., SideSeeing , StreetAware ). Implement edge computer vision for real-time analysis on sensor hardware. Design privacy-preserving solutions
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of the Research, Innovation and Dissemination Centers (RIDCs) supported by the São Paulo Research Foundation (FAPESP), with the Federal University of São Paulo's Medical School (EPM-UNIFESP) in Brazil as its host
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well as the design of new biotechnological tools for the delivery of engineered effectors against targeted pathogens. Studies will be carried out within the scope of the Biology of Bacteria and Bacteriophages Research
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for Innovation in Artificial Intelligence for Health (CIIA-SAÚDE), specifically in the subproject “Prediction of Clinical and Economic Outcomes through Semantic Representations Multimodal Patients Resilient
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additive manufacturing (especially with extrusion and photopolymerization processes) of scaffolds using experimental designs and technical standards; 3) Interpreting results obtained in item 2 with a deep
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related to staff position within a Research Infrastructure? No Offer Description One of the Research, Innovation and Dissemination Centers (RIDCs) supported by the São Paulo Research Foundation (FAPESP) in
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the Research, Innovation, and Dissemination Centre B³ (Biology of Bacteria and Bacteriophages), one of the Research, Innovation and Dissemination Centers (RIDCs) supported by the São Paulo Research Foundation
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Postdoctoral researcher in seismic petrophysical inversion for carbonate reservoir characterization.
Fapesp through the Energy Production Innovation Center (EPIC). Candidates must send a short CV to Prof. Emilson Leite ([email protected] ) highlighting activities relevant to this position. The email
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integrated data analysis” offers a post-doctoral position to design, develop and evaluate supervised and unsupervised machine learning models, which generate fuzzy rule bases with a focus on interpretability