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- University of Melbourne
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Field
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machine learning. Sense of responsibility and ability to communicate and integrate into multidisciplinary work teams. Financial component - According to the Table, contained in Annex I to the FCT
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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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://doi.org/10.54499/2023.11234.PEX , funded by national funds through FCT/MECI, under the following conditions: Scientific Area: Machine Learning applied in Applied to Fluid Dynamics Simulation Admission
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2 Oct 2025 Job Information Organisation/Company Instituto Politécnico do Cávado e do Ave Research Field Management sciences » Other Economics » Financial science Engineering » Computer engineering
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Artificial Intelligence, with an emphasis on developing methodologies and techniques for Evolutionary Computation and Machine Learning. Work Plan: State-of-the-art survey of Evolutionary Algorithms and Large
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Awards program aims to support growth and innovation in the next generation of diverse cancer researchers across Canada at the master's, doctoral, and postdoctoral levels. This program seeks to build
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real-world deployment scenarios and collaborate with global organizations to ensure practical implementation and scalability. Key Research Areas: Software engineering, AI/machine learning, IoT
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Research Studentships (for students of a Master or Integrated Master students) - (BL202/2025-IST-ID)
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | about 2 months agoengineering Researcher Profile First Stage Researcher (R1) Positions Bachelor Positions Country Portugal Application Deadline 4 Sep 2025 - 23:59 (Europe/Lisbon) Type of Contract Not Applicable Job Status Not
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that, they can be replaced by a declaration of honour. Preferential factors: • Expertise in machine learning, information retrieval, natural language processing. • Expertise in conversational models and systems
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rely heavily on the quality of the energy supplied to them. Failures in low-voltage cables or active equipment within the network can also lead to interruptions in machine operation and overall factory