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) to work on the development of an Amazonian Early Warning System (AmEWS) integrating Earth Observation data, process-based ecosystem models, and advanced machine learning approaches. The position is embedded
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with main workplace at UiT campus Tromsø. HMI has members from a variety of nationalities, and the working language is English. Contact For further information about the position, please contact
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documents as a single PDF, including a cover letter, curriculum vitae, copies of academic transcripts and degree certificates, and contact information for two references. Application should be sent via email
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to submit an application. A complete application includes : - Cover Letter - CV (month/year format) For more information contact: Yiliang Zhu, PhD at (YiZhu@salud.unm.edu ). For Best Consideration For best
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30 Mar 2026 Job Information Organisation/Company INSA Rennes Department Material Science and Engineering Research Field Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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the wind/renewable energy training and research elements of the CDT programme. Funded by Statkraft and EPSRC, this 4 year this PhD studentship, at the University of Strathclyde is in the area of data
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Applicants should submit: • Cover letter describing research experience and fit for the position • Curriculum vitae • Contact information for three professional references MQ: Bachelor's Degree with 1 year
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 13 days ago
28 Mar 2026 Job Information Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile First Stage Researcher (R1
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TypeFixed-termWorking TypeHybridAvailable for SecondmentNoClosing Date30-Apr-2026JD_Param11NoJD_Param12No Two 3.5 year PhD studentships in Artificial Intelligence in Medicine, or Health Data Science, funded
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carcinoma as a use case. The successful applicant will develop Bayesian statistical and machine learning methods for treatment response prediction using clinical information, molecular characterizations