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degree or equivalent qualifications in Engineering Physics. Technical Skills: Programming proficiency in Python and experience with machine learning frameworks such as PyTorch or TensorFlow; Experience
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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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generation methodologies to improve the robustness of Machine Learning (ML) models. Your role: Semantic segmentation and classification by ML: Explore and benchmark state-of-the-art semantic segmentation and
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.; - Develop skills in artificial intelligence and machine learning techniques for analyzing operational data and detecting anomalies, using foundational model approaches (e.g., GridFM project, LF Energy
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Institute of Systems and Robotics-Faculty of Sciences and Technology of the University of Coimbra | Portugal | 7 days ago
. Candidates should possess a strong background in power systems, multi-objective optimization and control (particularly MPC), and machine-learning–based time-series forecasting, along with proficiency in MATLAB
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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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, stringent layout design rules demand new design automation solutions beyond the actual state-of-the-art. The proposed work plan focuses on the thorough exploration of innovative generative machine learning
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of establishing relationships between signal sources and predicting commands; 6. Design of machine learning and adaptive models that ensure the continuous evolution of the system, increasing the autonomy and
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: Fraunhofer Portugal AICOS is seeking a talented Time Series Scientist to join our dynamic and multidisciplinary team within the Intelligent Systems Group , namely in machine learning and time series analysis
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13 (5 points); Bachelor Degree classification lower than 13 (2 points); B. Knowledge of Cyber-physical Systems, Automation, CAN Communication Protocol, Machine Learning, AI, Sensor Networks