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with researchers from machine learning and fire safety and material science in a truly interdisciplinary environment. Co-author scientific papers aimed at high-impact journals. Participate in
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chemical impact assessment through machine learning - DTU Sustain Kgs. Lyngby, Denmark Posted on 06/06/2024 Be the First to Apply Work with international front-runners in developing methods for assessing
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of machine learning methods for reduced order process model generation (experience with Gaussian process models is further desirable). Developing APIs and automated workflows for connecting numerical
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teaching within mechatronics. This could for example be within the following topics: Autonomous robots Dynamics and vibration theory Industrial control systems and automation Machine learning and AI
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central goal of the project is to develop explainable machine learning models that allow insight into the interaction between genetics and other types of data that can be used for developing tailored
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critically explore the governmental, technical, and ethical challenges that arise from these pressing developments. AIM focuses on generative AI and machine learning for mental health, with a particular
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critically explore the governmental, technical, and ethical challenges that arise from these pressing developments. AIM focuses on generative AI and machine learning for mental health, with a particular
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: Publish impactful work in leading journals and conferences in your field Teach, guide, and supervise BSc and MSc student projects, as well as supervise PhD students Actively participate in creating a robust
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. To overcome this challenge, neural architecture search and other ideas within the general field of automated machine learning have been proposed. We seek one or more PhD students(employed as PhD fellow if you
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with relevant data collected at industrial scale Apply AI / machine learning to support on-line deployment of the mathematical model for real-time prediction Using the model, investigate and prioritize