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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make buildings smarter and more sustainable? Join us to advance your career by working
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Job Description Are you passionate about leveraging IoT, machine learning, and optimization to make energy districts and communities more sustainable? We are looking for a highly motivated and
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and analysis, human-machine interaction, productivity monitoring, and proactive personalized feedback and learning methods (using augmented and/or virtual realities). We seek excellent candidates with
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Embedded AI, Edge AI, TinyML, and AIoT, that can be documented by a publication record in relevant venues. Solid understanding of state-of-the-art embedded machine learning techniques. Experience in system
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materials discovery, materials processing, and structural analyses. We also focus on educating engineering students at all levels, ranging from BSc, MSc, PhD to lifelong learning students. We have about 300
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(e.g., network calculus or similar timing-analysis methods) and/or dynamic reconfiguration (e.g., using Q-search, reinforcement learning, or metaheuristics). You may also contribute to developing
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approach will create a unique foundation for advanced data analysis, including AI, machine learning, and statistical modeling, aimed at uncover the key traits that define successful microbial biofertilizers
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opportunities, and proposal development. You can learn more about ESE and the future faculty positions here . If you are applying from abroad, you may find useful information on working in Denmark and at DTU
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spatio-temporal regularization, discrete tomography, low-dimensional latent representations and machine learning. The ultimate aim is to reduce the carbon footprint for the construction industry and enable
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Job Description Are you a cybersecurity researcher eager to push the boundaries of cyber-deception? Do you have expertise in cybersecurity, machine learning and/or cyber-psychology? This fully