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experience in common deep learning frameworks (e.g., PyTorch and TensorFlow) would be a benefit; The qualities to carry out independent research, demonstrated e.g., by the grades obtained in your (under
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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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processing, embedded systems, machine learning, and networked communication. Each PhD position corresponds to a dedicated research topic within the consortium. All doctoral researchers will benefit from joint
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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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(PSI), within the research group EAVISE. The project explores audio representation learning for low-resource settings. Recent advances in machine learning for audio have focused on learning
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you to apply. The opportunity to work on a challenging and advanced research topic, in a dynamic academic environment, to acquire research and project management skills, to network with leading
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) inconsortium/institutional seminars and national/international symposiums or conferences. Eager to carry out visitations (if required) to other laboratories (within Belgium or abroad) for learning new techniques
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international workshops and conferences, presenting and discussing your research globally. Teach and contribute: Provide support for teaching activities and teaching innovation. Build up and apply skills: Build
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bipedal robot that will learn to walk on soft and natural ground, such as sand and gravel. The controller design will include knowledge of the type of ground the robot walks over, and how the substrate
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knowledge of Microsoft Word, Excel and PowerPoint. You have experience in, or are willing to learn MATLAB. You hold the FELASA B certificate, or international equivalent or you are willing to follow a