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dialogues, analyses of spatial data, validation and testing the indicators on case-studies. You will develop maps of nature values to contribute essential knowledge for sustainable marine coastal planning and
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experience through field experimentation, data processing, statistical analysis, scientific writing, and the communication of research findings. You will work closely with researchers at SLU and with
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different types of experimental data to establish reliable methods for identifying physically meaningful model parameters and assessing model accuracy under dynamic operating conditions. In a later stage
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Curriculum Vitae - Your most recently updated C.V. Cover Letter Statement of Research Statement of Teaching (Optional) Reference requirements 3-5 required (contact information only) Apply link: https://apol
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develop a physics-informed digital-twinning approach to better characterize these dynamics and estimate relevant electrical and control parameters from transient voltage and current data. Your tasks will
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 28 days ago
anomalous state. We are seeking a postdoctoral scholar to conduct in-depth analysis of stratospheric data, using data from the Microwave Limb Sounder (MLS) as well as complementary datasets like the
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for a postdoctoral fellow position in the Laboratory of Systems Pharmacology ( LSP ; https://labsyspharm.org/ ), part of the Harvard Program in Therapeutic Science, at Harvard Medical School in
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observational field data, experimental data, and field experiments. Salary is $70,500 annually, plus benefits. Expected start date is mid-June 2027. For examples of our research, see our faculty pages: https
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and Machine Learning , with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable
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on occurrence data, chemical properties, environmental persistence, mobility and available samples; ii) applying target, suspect and non-target screening using LC-HRMS to identify known and previously