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digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design
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analysis Close collaboration with an interdisciplinary team. Research and teaching efforts at a section and departmental level as appropriate and relevant (e.g., teach and supervise MSc and PhD student
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simulations using, e.g., COMSOL, Lumerical, or other Maxwell solvers. Experience with machine learning algorithms is an advantage but not required. General qualifications Scientific production and research
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Greenland. Learn more on aqua.dtu.dk . Technology for people DTU develops technology for people. With our international elite research and study programmes, we are helping to create a better world and to
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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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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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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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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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the above-mentioned research areas (e.g. scp-MS, cell heterogeneity, computational proteomics, etc.) Foster national and international collaborations, both outside and within the university Teach in