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postdoctoral fellowships. 1. Robust Methods for Volatility Estimation with High-Dimensional Data — design, implementation, and computational analysis. Supervisor: Prof. Luiz Koodi Hotta. 2. Forecasting Methods
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methods to ultimately let dermatologists continually update multi-modal machine learning models. Our research objectives are to 1) develop novel model editing methods for multi-modal models, with a focus on
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Barts Charity, aimed at realising the full potential of Genes & Health and other large-scale health datasets to estimate rare disease prevalence and identify genetic associations in South Asians. About
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design or experimental methods and machine learning. The term of appointment is based on rank. Positions at the postdoctoral rank are for one year with the possibility of renewal pending satisfactory
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learning techniques (RF, XGBoost, NN, SISSO) to screen all the possible compositions of the half-Heusler family in order to find high ZT materials. - Propose new ML methods. - Perform DFT calculations
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
$62,000- $70,000 Proposed Start Date Estimated Duration of Appointment 12 Months Position Information Be a Tar Heel! A global higher education leader in innovative teaching, research and public service
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17 Nov 2025 Job Information Organisation/Company Instituto Politécnico de Bragança Department Gabinete de Apoio a Projetos Research Field Engineering » Computer engineering Researcher Profile First
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 10 hours ago
Researcher - Mixed-Methods Diabetes Care and Aging Research Vacancy ID PDS004726 Full-time/Part-time Full-Time Permanent Hours per week 40 FTE 1 Work Location Chapel Hill, NC Position Location North Carolina
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on this position will be the development and implementation of novel statistical and computational methods with applications to system biology problems and spatial transcriptomics datasets. The work will involve
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peer-reviewed journals and conferences. Preferred Qualifications: Experience with black-box modeling of wind turbines and converter-based power systems. Knowledge of Lyapunov-based methods, nonlinear