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decision-making. Working with real-world data from Alliander, you will publish at leading machine learning venues while building tools with tangible impact on the Dutch energy sector. The Dutch energy
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Are you fascinated by how machine learning can enhance control without compromising safety or stability? As a PhD candidate, you will develop scalable methods for expressive and flexible neural
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of professionals and students. Together, we create knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea
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demonstrable experience with programming in Python and implementing statistical or machine learning algorithms. You have experience with software development practices such as testing and version control with
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knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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related field with a strong quantitative focus. Strong programming skills in Python and demonstrated experience with machine deep learning frameworks (for instance, PyTorch or TensorFlow), preferably
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on the field can be derived from first principles, and how these constraints can improve the technique's performance, particularly when embedded in modern machine learning models. The ultimate goal is to
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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied
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theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior knowledge on nonlinear dynamics, dynamical systems theory
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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal