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are an NSF-funded research project. The primary purpose of the position is to build a digital twin for national-scale field-level crop monitoring, modeling, prediction, and decision support and automation
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the following training will be considered PhD in computer science, machine learning, AI or related computational field, or, Ph.D. in a health-related discipline with experience in experimental science, devices
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on JavaScript in your browser and try again. UiO/Anders Lien 15th August 2025 Languages English English English PhD Research Fellow in Machine Learning Apply for this job See advertisement About the position
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. The researcher would be expected to have knowledge of protein structure, protein ligand binding, machine learning and expertise in workflow development. Information generated by the project will be widely
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technology management, or smart grids. Experience in development of mathematical meta-models, control strategies, optimization methods and algorithms, data analysis and machine learning techniques, techno
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well as in a collaborative, team-oriented environment. Preferred Qualifications: Prior experience working with mouse models of cancer is strongly preferred; candidates without prior experience will be
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clinically validate innovative predictive models utilizing AI and machine learning; test cadaveric anatomy study implementation Complete Data collection and finalize evaluation of AI predictive models
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communication resources to train the federated machine learning model efficiently. She/he will investigate realistic scenarios including non-iidness of data distribution, system heterogeneity, and dynamic
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. Department Contact for Questions Miranda Lockwood, SHRM-CP Human Resources Business Partner mjlockwo@iu.edu Additional Qualifications Experience with machine learning and AI models. Ability to communicate
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programme. To acquire, analyse, interpret and evaluate research findings/data using approaches, techniques, models and methods selected or developed for the purpose. To establish a national reputation and