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research and experimental work in the fields of sensor networks, biomedical engineering and machine learning with focus on: Utilisation of Inertial Measurement Units (IMUs) in human movement including data
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of Informatics and Computing Engineering; ii) Knowledge of machine learning techniques and interest in developing skills in the CausalAI topic; iii) Some experience or interest in machine learning operations
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of Informatics and Computing Engineering; ii) Knowledge of machine learning techniques and interest in developing such skills; iii) Some experience or interest in machine learning operations (MLOps); iv) Good
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 14 days ago
candidate demonstrates proven experience in machine learning, deep learning, and modeling. Additional Information Benefits Monthly maintenance allowance: According to the values for Research Fellowships
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conditions: Scientific area: Informatics Admission requirements: Master in Informatics Engineering (or related field). Experience in Machine Learning and Natural Language Processing are preferred factors
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 1 month ago
(PIDDAC Workplan: This work aims to develop new machine learning methods for breast diagnosis. Specifically, multiple instance learning (MIL) applied to three different image modalities: (i) mammography
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3 Apr 2024 Job Information Organisation/Company INESC ID Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Country Portugal Application Deadline 17 Apr
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(2 points); B. Knowledge of Cyber-Physical Systems, Automation, Sensor Networks, Machine Learning and Artificial Intelligence (1 to 5 points); C. Knowledge of intelligent systems based on AI, mobile
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months ago
upon a recent quantum map-retrieving algorithm inspired by machine learning techniques. Our approach will involve extracting the complete Liouvillian generator and identifying the Hamiltonian and
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of historical documentation – 30%. c) Preferential Factors (FP): Enrollment in a master's degree in medieval history; willingness to learn new computer skills and carry out research on the project's themes