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of specific 2D functionalization strategies, we have a broad and flexible focus when it comes to the employed methodologies (empirical models, DFT, many-body perturbation theory, machine-learning) the target
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Dynamics (AIMD), and Machine Learning (ML) tools to develop theoretical electrocatalytic frameworks. Hereby, the project will challenge existing research on catalysis, move the boundary of fundamental
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assessments. The exceptional availability of Danish Big Dataset on health outcomes, consumption and sustainability. A unique combination of mass balance-based Source-to-Impact Models and Machine Learning
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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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the Department of Economics and Business Economics, we are looking for lecturers who can teach at Bachelor or Master’s level within, but not limited to, the following fields: Business Intelligence Machine and Deep
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focus on (i) generative models and machine learning of structure-property relations (ii) crystal point defects for quantum technology applications (iii) excitons and nonlinear optics. You will work in an
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environmental engineering. Postdoc position in advancing chemical impact assessment through machine learning - DTU Sustain Kgs. Lyngby, Denmark Posted on 06/06/2024 Be the First to Apply Work with international
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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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: 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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for energy conversion and storage applications. You will work with around 25 colleagues with diverse backgrounds in computational and experimental science, machine learning, and artificial intelligence. We