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of video and low-cost sensor technologies to capture subtle movement patterns, creating a rich dataset for AI-driven analysis. Machine learning, deep learning, computer vision and multimodal AI methods will
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Position Description The project will focus on the development and application of advanced data-analysis techniques for gravitational-wave science, including machine learning and deep learning
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mechanisms that integrate queueing theory, traffic modelling, machine learning, and network-performance prediction for improving latency, reliability and fairness to support mission‑critical services
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, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, age, status as an individual with a disability, military or veteran status
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21 Sep 2026 Job Information Organisation/Company CMU Portugal Program - FCT Research Field Engineering » Computer engineering Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates to experimental data and ability to automate data storage
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of the following criteria: Technical competencies Knowledge of machine learning / AI methods and their applications to experimental data; Knowledge of data science (statistics and quality control) as it relates
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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doctoral degree Collect, structure and assess relevant sensor, operational, maintenance, incident and cost data Develop and validate statistical, causal and/or machine-learning methods and turn the results
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to conduct research activities in the field of Brain-Computer Interfaces, in the scope of the project “BCI4ALL”, co-funded by national funds through the Portuguese Foundation for Science and Technology, I.P