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are to enhance barley and oat productivity, quality, and stress resilience by combing traditional, molecular, and genomics methods. You will collaborate with other scientists in the unit and other institutes
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Applications are invited for a Research Fellow position within the Astronautics Group, in the Department of Aeronautics and Astronautics. The post will work on a collaborative project between the
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within the Division of Artificial Medical Intelligence of Department of Ophthalmology in the University of Colorado School of Medicine. We focus broadly on quantitative and machine learning techniques in
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agents that collaborate with human analysts in exploratory data analysis, dashboard authoring, and visual sensemaking. Design, implement, and evaluate visualization dashboards and visual analytics systems
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 8 days ago
curiosity into ideas that have shaped Australia and our region. Learn more about ANU, our history and the community that has shaped us: ANU at 80 The Australian National University is seeking a motivated
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, that can be realised using cloud compute infrastructure and other novel deployment architectures. Given our team's existing research skillset in novel machine learning approaches, we are recruiting a
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background in geomodelling, geophysical and geotechnical investigation, geomechanical engineering, and machine learning. You will be expected to work effectively on a geophysical/geomechanical project, to
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arrangements to help manage your work-life balance, ongoing learning and development opportunities to grow your career; an inclusive and supportive culture and environment to work in, both online and on campus
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in mathematical modelling and Bayesian inference while learning from three collaborating chief investigators. You will also build your publication record and professional networks through seminars
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, clinical and sensor data processing, quantitative image analysis and machine learning. They will establish and maintain robust research databases and FAIR-compliant data management processes for large, multi