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to emerging or re-emerging diseases. Proficiency in programming languages such as Python, R, SQL, or similar tools for data analysis and model development. Experience in working with large and complex datasets
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of computational neuroscience concepts - Expertise in dynamical systems theory - Knowledge of machine learning - Experience with neural data analysis ### Technical Skills - Advanced scientific programming (Python
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analysis and inversions of seismic data and possess sufficient specialist knowledge in the discipline to work within established research programmes. They will also be expected to manage their own academic
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10 Apr 2026 Job Information Organisation/Company NEW YORK UNIVERSITY ABU DHABI Research Field Mathematics Physics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
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candidates will hold or be close to completion of a PhD/DPhil in seismology (thesis must be submitted before an offer is made). They should have relevant experience in analysis and inversions of seismic data
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geospatial modeling approaches to analyze urban environmental processes. • Apply machine learning and geospatial data analysis techniques to large Earth Observation datasets. • Produce high-quality
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technical reports, summaries, protocols, and qualitative analyses. Develops systems, processes, and procedures for timely data collection. Provides statistical analysis and data management support scientific
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Max Planck Institute for Political and Social Science, Göttingen | Gottingen, Niedersachsen | Germany | about 12 hours ago
input, fieldwork oversight, and analysis of large-scale cross-national survey data; Oversee key aspects of implementing an international teacher survey, including coordination with external survey firms
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literature search and preregistered meta-analysis Coordinate MRI data collection with the technical team at the Leiden University Medical Center (LUMC) Perform fMRI preprocessing and statistical analyses
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demonstrated experience in computer vision or analysis of pathology images. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model