89 machine-learning-"https:"-"https:"-"https:"-"https:"-"ISCTE-IUL" positions in Belgium
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extraction to support discovery. Collaborate with researchers to identify opportunities where generative AI and LLMs can accelerate scientific progress. Work with the Head of the Machine Learning Expertise
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machine learning processing of the spectroscopic data • The optical design and development of novel custom spectroscopic sensors benefitting from freeform optics. • Integration of the in-situ
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implementing signal processing algorithms specifically tailored to analyze signals that contain interfering impulsive content, often encountered in data coming from main and pitch bearings. Machine learning
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that reduce raw data at the sensor level. You will develop AI and machine learning algorithms for anomaly detection, pattern recognition, and efficient data compression. To ensure practical usability
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for environmental epidemiology (Epi, survival, sf, gstat, mgcv) and causal inference (dagitty, MatchIt), as well as contributing to reproducible, scalable data pipelines. Machine learning integration: Exploring ML
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management, and machine learning approaches for process monitoring and control For this function, our Brussels Humanities, Sciences & Engineering Campus (Elsene) will serve as your home base.
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be analysed using network analysis and machine learning. Empirically, the project aims to understand what China, the US and Europe are doing to compete in semiconductors, cloud computing and space
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. You can work in a group as well as on your own initiative. You have knowledge in machine learning for vision. Hands-on experience with image acquisitions and different types of cameras (visible
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experience with quantitative research methods, including psycho-physiological and behavioral measures and advanced statistical (and/or machine learning) methods. You have a high level of proficiency in English
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. You are fluent in Python, machine learning, and deep-learning tools (e.g., TensorFlow, PyTorch). You can speak and write fluently in English. A background in hydroclimate extreme event analysis is