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statewide and national learning networks (e.g., National Child Traumatic Stress Initiative Evaluation Community of Practice, Utah Early Childhood Mental Health Workforce). Develop mentoring, and supervision
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of statistics and machine learning. Modern vessels produce vast amounts of multivariate data streams. The project addresses the development of trustworthy statistical and machine learning methods for anomaly
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focuses on detecting underwater acoustics using AI methodologies. Additionally, CFD simulations combined with physics-informed machine learning will also be examined. Several research and industrial
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are expected to acquire basic pedagogical competency during their fellowship period within the duty component of 25 %. Project description and work tasks The Postdoctoral Research Fellow will broadly address
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Norway, NTNU will arrange for you to acquire such competence during the employment period. In such cases, you will also be assigned relevant teaching as part of the career-promoting work. The appointment
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, hazards in e-waste disposal and management, and policy evaluation. The post-doctoral fellow will have numerous research training opportunities, all with the goal of developing independent and highly
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Center for Biologics Evaluation and Research (CBER) | Silver Spring, Maryland | United States | 2 days ago
for diverse career options after the training period. Flexibility and a willingness to learn new techniques is a desirable quality in the applicant. Mentor: The mentor for this opportunity is Zuben E. Sauna
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, robotics and machine learning, focusing on fundamental aspects as well as on applications in multidisciplinary contexts. This position is part of the DRIVE project, funded by the Research Council of Norway
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effectively exploited, possibly using some kind of machine learning algorithm, provides more accurate data than traditional data collection methods, e.g. paper-based surveys. This data is valuable to several
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of Oslo’s Department of Informatics (IFI) and is hosted by the Network and Distributed Systems Research Group (ND) with co-supervision from IFI’s Machine Learning section and the University of Inland