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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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and 10 research sections. We broadly cover digital technologies within mathematics, data science, computer science, and computer engineering, including artificial intelligence (AI), machine learning
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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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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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(e.g. using COBRApy or related toolboxes), or a strong motivation to develop this expertise. Data science, AI/ML, and digital surrogate models Experience with data science and machine learning, including
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intelligence (AI), machine learning, internet of things (IoT), chip design, cybersecurity, human-computer interaction, social networks, fairness, and data ethics. Our research is rooted in basic research and
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and have synergiccollaborationeffects. Weexpect a motivatedearlycareer researcher with stronginterest and experience with GIS/earth observation/climateprojection data as well as machine learning models
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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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written and spoken Willingness to engage in interdisciplinary collaboration and fieldwork Advantageous: Knowledge of bat ecology and species identification Experience with machine learning or automated
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the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning for improving