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Research Associate to develop, scale, and apply artificial intelligence (AI) and deep learning (DL) models for power grid systems. The successful candidate will contribute to scalable AI workflows for grid
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IMADA uniquely brings mathematicians and computer scientists together within a single department to foster theoretically well-backed, high-quality data science research. The department is home to numerous
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Department of Electronic Systems employs more than 200 people, of which about 90 are PhD students, and about 40 % of all employees are internationals. In total, it has more than 600 students in its BSc and MSc
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initiatives. Person Specification Qualifications First degree in a relevant discipline (e.g. Environmental Science, Geography, Earth Sciences or related field) PhD (or near completion) in a relevant subject
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imaging, ideally with the ability to carry out advanced measurements at the Advanced Photon Source. Experience with in-situ characterization and experimental apparatus development is especially valued. In
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hold a PhD in machine learning, computer science, bioinformatics or equivalent. You combine strong analytical skills with the ability to work independently and lead collaborative efforts. You are a team
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suitable for academic, policy and public audiences Lead and co-develop submissions to peer-reviewed journals Your profile Required: PhD in geography, sustainability science, environmental governance, science
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for candidates with a PhD from another university than Aalborg University. The positions are open to outstanding candidates who wish to develop and lead their own independent research project within one
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Infrastructure Computer Vision Data Analytics for the Built Environment You should possess: A completed PhD in a relevant discipline. Strong research expertise in digital engineering and built environment research
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modeling to advance sustainable agricultural systems. Required Minimum Qualifications: PhD in agronomy or related science. Preferred Qualifications: Experience authoring and contributing to peer-reviewed