87 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"UCL" positions in Belgium
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multiple symbolic fields, including official political discourse, academic debates and selected cultural outputs. Methodologically, it adopts a mixed-methods approach, combining machine-learning–enhanced
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fully funded PhD position in machine learning, AI, and data science for public health within the Electronics & Informatics Department (ETRO) of Vrije Universiteit Brussel (VUB). The PhD is embedded in
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, collaborative science Experience with tools for qualitative and quantitative analysis; experience and practice with machine learning and Artificial Intelligence are also considered assets Language requirements
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the research team in the area of Swarm Intelligence, Reinforcement Learning and Optimization Techniques. As a Postdoctoral researcher, you will: Lead cutting edge research in Swarm Intelligence and Machine
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, incorporating transient tribological changes. Creating machine-learning-based surrogate models to enable rapid efficiency and lifetime predictions under realistic operating conditions. Validating the developed
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of Applied Mathematics: Statistics Position You will work actively on the preparation of a PhD thesis in the field of statistics and machine learning. The envisioned topic is practical challenges of causal
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with Artificial Intelligence and deep learning concepts for robotics computer vision, tactile sensing, reinforcement learning Experience with robotic simulation tools e.g., ROS, Gazebo, Mujoco, IsaacSim
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of competitive research proposals. You should have experience in the following areas: Applied Machine Learning for Autonomous Systems: Experience developing and deploying ML models for perception, prediction
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(including pig) and tissue fluent user of computer software (e.g., Microsoft 365, SPSS/Prism, EndNote,…) flexibility to learn new skills and develop novel approaches for analysis ability to work independently
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: *Extensions of the eligibility period are possible based on documented absence for parental leave, long-term illness, military service or clinical training. Check the ERC Work Programme on the ERC website