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the lifecycle of industrial systems. As machine learning sees broader adoption, companies are increasingly required to ensure the safety of machine-learning-enabled systems. The reliance on training data and the
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how a novel machine learning-based methodology leveraging reinforcement learning with human feedback and multi-objective optimisation can be realized to generate new and even improve existing work plans
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well connected to the machine and transportation, high precisionindustriesand I am eager to learn how academic research can be linked to industrial innovation roadmaps. During my PhD I want to grow
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citation record must be focused on AI; or alternatively (B), machine learning engineers with an AI-focused PhD and demonstrated 2-year industry experience in AI development Applicants must have in-depth
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, Ultrasound and Vibration, Aircraft Structures, Damage Assessment, Structural Health Monitoring, Structural Health Prognosis, Bayesian Statistics, Machine Learning Informal enquiries prior to making
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are comfortable working with Git and API tooling, such as Postman. You have experience in machine learning, NLP/LLMs, multimodal systems, computer vision, or scraping. Having experience in data science
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of data analysis, time series analysis, machine learning and algorithm development. have knowledge on machine learning with Python or MATLAB. are very fluent in English, both spoken and written. possess
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occupational asthma, dust lung, auto-immune diseases, cancer, etc). · Strengthens existing research lines and brings complementary and/or additionally new expertise by working closely with the members
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renewable energy generation.KU Leuven leads Modelling and Optimization, which focuses on: Developing hybrid models combining first-principle and machine learning approaches. Creating predictive frameworks
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in international research visits if needed. We are looking for a highly motivated researcher with: A PhD in machine learning, computer vision, remote sensing, glaciology, climate science, or a related