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cycle or non-award courses of Higher Education Institutions. Preference factors: Prior knowledge of psychophysiological variables. Previous work with ECG signals and field data collection using wearable
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to grant holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - broaden the knowledge of the state
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factors: - Experience in designing and implementing key-value stores; - Solid knowledge on order and durability guarantees for efficient logging systems.; Minimum requirements: - Solid knowledge
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on the applicants' enrolment in study cycle or non-award courses of Higher Education Institutions. Preference factors: - Knowledge of data compression and/or deduplication techniques. Minimum requirements
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Institutions. Preference factors: - Experience in designing and implementing storage systems; - Solid knowledge of heterogeneous storage stacks. Minimum requirements: - Knowledge on operating systems and
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to grant holders" (https://www.inesctec.pt/pagamento-propinas-bolseirosEN ) The grant holder will benefit from health insurance, supported by INESC TEC. 2. OBJECTIVES: - broaden the knowledge of the state
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-award courses of Higher Education Institutions. Preference factors: Machine Learning Knowledge. Knowledge of signal processing and machine learning libraries (e.g., PyCaret, scikit-learn). Minimum
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); - Solid knowledge on operating systems; - Solid knowledge on distributed systems; - Experience with the C/C++ programming language. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS: Selection criteria
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repositories and mechanisms such as GitHub Actions.; Minimum requirements: - Knowledge of operating systems and data storage systems; - Experience in developing data storage features and optimizations
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electrical engineering projects.; - Knowledge of libraries for developing and training ML models; Minimum requirements: - Knowledge of computer programming. 5. EVALUATION OF APPLICATIONS AND SELECTION PROCESS