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will be part of a research environment focusing on integrating multi-source satellite remote sensing data and developing novel algorithms to quantify agroecosystem variables for environmental
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biodiversity assessments and methodological development at Aarhus University. Your profile Applicants should hold a PhD in ecology, population or conservation genetics, evolutionary biology, bioinformatics
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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and statistical subjects such as programming, algorithms, machine learning, and artificial intelligence. Define and supervise projects for Master and PhD students. Attract external funding from national
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interface, and all the way to quantum algorithms and applications. The long-term mission of the programme is to develop fault-tolerant quantum computing hardware and quantum algorithms that solve life
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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description You will be contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will
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conditions for art and culture. Possible focal areas include AI and algorithmic creativity, digital media aesthetics, data-driven culture, new forms of the dissemination of art, literature, theatre and music
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analysis to translate THz signals into optical material properties such as refractive index and absorption coefficient. Development of machine learning algorithms for material classification. Exploration
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is an advantage but is not required. A strong interest in evolutionary principles, ecological principles, and data science are expected. The applicant must be interested in working in