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and execution of a seminar series, tentatively titled “Présence(s) Radicale(s),” to take place during the final months of the period of employment (October 2027 – May 2028). This monthly seminar will
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Doctoral Associate. Prof. Kaelber is the 3DEM Advisor to the RCSB PDB (Protein Data Bank). The postdoctoral associate will attend relevant seminar series on this and other campuses of Rutgers related
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the relationship between international competition and market freedom. The project launches in 2026, the 250th anniversary of the publication of The Wealth of Nations, and includes an international workshop series
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 9 hours ago
demonstration of experience in quantitative research. PREFERRED: Experience with machine learning methods for time-series analysis; anomaly and changepoint detection, or instrument diagnostics; familiarity with
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contribute intellectually to new research directions within the SAGE Lab. Preferred Experience with multimodal sensing, computer vision, time-series analysis, uncertainty quantification, model calibration
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website is available here: IS2H4C PROJECT Financial Forecasting & AI: Use scenario case analysis, simulation, time series models, and/or AI-based approaches to forecast cash flows and support financial
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related field by the start date. Research experience with seismic or other geophysical time-series data, as evidenced by peer-reviewed publications, thesis chapters, or conference presentations. Experience
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calculations. The UCC logistics models simulate installation, operation and maintenance, and decommissioning task by task against hourly wind and wave time series spanning the project lifetime, with Monte Carlo
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against hourly wind and wave time series spanning the project lifetime, with Monte Carlo simulation over weather years and component time-to-failure. The models are currently implemented in MATLAB with
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for advanced statistical and time-series analyses. They will analyse behavioral, EEG and eye-tracking data collected during prolonged experimental sessions. The research will focus on the modelling and