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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 4 days ago
Regulation (Regulation No. 950/2019). Selection process Selection will be based on curriculum evaluation. Evaluation Criteria Curriculum Vitae: 80% Motivation Letter demonstrating compliance with all admission
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Instituto de Geografia e Ordenamento do Território da Universidade de Lisboa | Portugal | 4 days ago
). Selection process Selection will be based on curriculum evaluation. Evaluation Criteria Curriculum Vitae: 60% Bachelor's Degree Classification: 5% Master's Degree Classification: 15% Motivation Letter
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. The candidate should also indicate the e-mail address to be notified for all purposes within the scope of this procedure. Applications should be sent by email to Doctor Valter Silva ([email protected] ). 14
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identified in the contractualization process. Other benefits: Reimbursement of Voluntary Social Insurance, if the candidate chooses to receive it, corresponding to the 1st level of discounts (for research
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by the following documents: Curriculum Vitae, certificate of qualifications, declaration of honor, motivation letter and other supporting documents deemed relevant. They shall also indicate the e-mail
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of the proposed solutions. Activities will include the implementation and evaluation of algorithms for signal processing, detection, correlation, localization, and tracking of acoustic sources, as
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of the Foundation for Science and Technology (RBI-FCT), by the Research Fellow Statute (EBI), by the Norms for Grant Assignment and Management within R&D Projects, by the Code of Administrative Procedure (CPA), all
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knowledge of machine learning models and Python tools for signal processing and machine learning. General knowledge of system architecture and APIs. Previous knowledge of physiological signal processing. 5
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producing reports and scientific papers. Minimum requirements: Knowledge of digital signal processing, data analysis, and signal or data compression methods; Knowledge of mathematical and statistical signal
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experience employing qualitative methodologies for data collection, processing and analysis; Proven experience in science communication, institutional communication and/or communication for research units