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, 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-level programming, developing prototype
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Postdoctoral Researcher Position in Ecological Knowledge-Guided Machine Learning at Aarhus Univer...
quality modelling, with focus on Knowledge-Guided Machine Learning. The position is a rewarding opportunity to be integrated in an excellent freshwater group. The department’s research and advisory
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/or large genetic datasets. This may include genetic analyses, causal inference, epidemiological analyses, and clinical prediction modelling using machine learning approaches, and development
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or similar. Experience in handling dynamic modelling and control, experimental setup and testing, Digital Twin and Machine Learning Publication experience Collaboration and/or management skills Communication
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, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted
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within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer
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key agroecosystem variables. These variables include cover crop growth, crop nitrogen, yield, and tillage practices. You will develop novel algorithms to integrate data-driven machine learning and
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polar orbit, passing near the poles about 15 times per day and regularly observing the CIFAR study region. Its payload - two optical cameras, a thermal camera, and onboard machine-learning capabilities
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at the top venues of machine learning research. Responsibilities and qualifications You should have prior experience with machine learning from both a theoretical and practical perspective. Experience in one
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following thematic areas: • AREA 1: Machine learning and AI-driven methods for design, simulation, and optimisation in architectural and construction engineering. • AREA 2: Robotic and additive