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The postdoctoral researcher will work with computer-based analytical methods and large databases to develop theory and methodology for utilising aggregated data from archaeology, genetics, and linguistics, thereby
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Engineering, or related. Strong experience in ODE/PDE modeling and simulation (MATLAB, Python, or R). Experience withnumerical methods, optimization, parameter estimation, and sensitivity and uncertainty
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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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the framework of the ANR EmergeNS whose aim is to understand, through mathematical and computer models, the role that autocatalysis, multistability and spatial heterogeneity may have played in the emergence
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concrete (corresponding to 40% of cement use) and CEM I cement, leading to inaccuracies in estimating CO₂ capture, especially for other cement-based materials and modern blended cements. This project will
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Responsibilities: Build and analyze dynamical system models (multiscale, QSP, PBPK, PK-PD). Apply numerical methods, optimization, and parameter estimation to calibrate models to experimental/clinical data. Perform
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mixed methods. Contribute to the HCI and EdTech research team (https://www.tugraz.at/en/institute/hcc/research/research-groups/team-pammerschindler ). Engage in interdisciplinary collaboration with
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Computer Engineering. Level Scope: After earning a Ph.D., the next step in the academic or research career path is often a postdoc. A postdoc is a continuation of a researcher’s training that enables them
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 3 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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environment The Brain Imaging & Neuro Epidemiology group (BraINE) develops advanced methods for medical images analysis, combining computer vision, radiomics and deep learning approaches. The team has a double