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Job Description Job Responsibilities: -Design and implement AI/ML models to analyze large-scale agricultural datasets (e.g., field trials, satellite imagery, IoT sensor data). -Develop pipelines
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data to solve real-world environmental challenges? Join a cutting-edge international collaboration aimed at transforming wildfire preparedness in New Zealand and beyond. We are seeking a highly motivated
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn't imagine the future, we invent it. If you're passionate about joining a community that challenges the
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) to large-scale biomedical datasets. These models will be used to work with different types of data from the healthcare and biological domains, including genomic profiles, and clinical event sequences
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, with a particular emphasis on Urban Resilience to Climate Risks. Current research themes include: • Adaptation of People: Leveraging big data and computational methods to analyze adaptation behaviors and
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University & Research is the university and research centre for life sciences. The themes we deal with are relevant to everyone around the world and Wageningen, therefore, has a large international community
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and complex information spaces, for example in biochemistry, humanities, or software engineering. Our vision is to attack the big data challenge by a combination of human-centered data analysis and
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centre for life sciences. The themes we deal with are relevant to everyone around the world and Wageningen, therefore, has a large international community and a lot to offer to international employees
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member of the ‘Blackholistic’ team (Oxford-Amsterdam-Radboud) which includes relativistic simulations on all scales from black hole to large scale jets, as well as analysis of data from the Event Horizon
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                Leibniz Institute for Plasma Science and Technology | Greifswald, Mecklenburg Vorpommern | Germany | 17 days ago
their immunogenicity; Develop analysis strategies for large data sets and correlation matrix using programming languages (R, Python, SQL, etc.); Scientific supervision of undergraduate and doctoral