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reproduction; 5. Experience in light microscopy and image analysis techniques (machine learning – FIJI, deep learning). Non-compliance with these requirements invalidates the application. Provision of false
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Ciência e a Tecnologia, I.P., in force (https://former.fct.pt/apoios/bolsas/docs/RegulamentoBolsasFCT2019DR.pdf ). Monthly Allowance: 701,12 €, according to the table of values of grants awarded directly by
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. University of Algarve, 22 of April of 2026 The Principal Investigator Doctor André Miguel Duarte Where to apply E-mail bolsascima@ualg.pt Requirements Research FieldEnvironmental scienceEducation LevelMaster
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programming, and/or human-computer interaction (UX), and/or application of Machine Learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. 3. Financial
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. With the support of machine learning algorithms and log analysis applied to traffic metadata and communication flows, it ensures system resilience for both legal and regulatory compliance as
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in the project proposal for Profile 7, in particular: Task3: Multimodal Data Analysis and Machine Learning; Task4: Coating Optimization and task: Dissemination. The work will focus on the study and
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for 1 research grant within the framework of project “Understanding Machine Learning Systems”, financed by Faculdade de Engenharia da Universidade do Porto, under the following conditions: Scientific Area
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: familiarization with the workflow platform and machine learning concepts; development of web interfaces for data silo registration and federated training sessions monitoring; implementation of back-end components
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on scientific projects. Posts on machine learning topics in unbalanced domains. 4. Work Plan: 4.1. The purpose of this contract is to perform the following tasks: Definition of the methodology for Natural Capital
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Instituto de Investigação e Inovação em Saúde da Universidade do Porto (i3S) | Portugal | 2 months ago
networks or similar machine learning technologies applied to DNA; Preferential: Experience with transcription factor motif discovery; Proficiency in high-throughput sequence alignment methods; Candidates who