194 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Université de Bordeaux " Fellowship scholarships
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 13 days ago
application (https://ist-id.pt/recursos-humanos/bolseiros/#documentos-relacionados ); ii) Curriculum Vitae; iii) academic degree certificate, where applicable; iv) proof of enrollment at a course that does not
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 13 days ago
. The contract is not renewable in this category. It is mandatory to formalize applications with the submission of the following documents: i) B1 Form – Fellowship application (https://ist-id.pt/recursos-humanos
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compression, event-based or neuromorphic vision, signal processing, machine learning or deep learning for visual data. - Motivation for research and scientific dissemination. - Good communication skills in
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Computadores: Investigação e Desenvolvimento em Lisboa” is a Research and Development and Innovation Organization (R&D+i) in the fields of Computer Science and Electrical and Computer Engineering. INESC-ID’s
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innovation in the maritime sector. Contest Procedure Applications must be exclusively submitted on the admissions platform of the Instituto Superior Técnico at https://fenix.tecnico.ulisboa.pt/fenixedu
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communication, scientific dissemination and technical reporting activities of the project. Where to apply Website https://pica.cineca.it/ Requirements Additional Information Eligibility criteria Eligible
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tumors and metastases to investigate intra-patient heterogeneity. Genomic data will also be integrated with the single-cell datasets available. Where to apply Website https://pica.cineca.it/ Requirements
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potential. Additionally, the study aims to characterize molecular variability both within individual patients and across different patients. Where to apply Website https://pica.cineca.it/ Requirements
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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to sign the contract. More information is available on: https://www.dges.gov.pt/pt/pagina/reconhecimento . Workplan and the objectives to achieve: This work aims to develop a numerical approach based on