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specific applications. This project addresses the scientific and methodological challenge of converting InSAR observations and estimates into actionable, application-specific information. The postdoc will
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have been completed earlier. Additional requirements: Very good oral and written proficiency in English. Demonstrated experience in computational methods, particularly in deep learning and computer
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University of New Hampshire – Main Campus | New Boston, New Hampshire | United States | about 2 hours ago
, including transparency, blending, and perceptual separability. Develop and evaluate methods for perceptually grounded symbology selection, including simulation-based assessment across multiple background
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computer vision methods such as optical flow or motion estimation Experience with geospatial data processing (NetCDF/CF, GeoTIFF, xarray, GDAL/rasterio) Experience with GPU computing or deep learning
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include: Intrinsic uncertainty estimation in MLFFs (epistemic & aleatoric uncertainty) Negative log-likelihood and calibration methods for force-field training Feature-space and orbit-based analysis
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addition to salary, our Total Rewards benefits and Compensation Estimator give you a clear view of the complete package. The appointment is one year, with the possibility of renewal for a second year (up to two
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22 Apr 2026 Job Information Organisation/Company Radboud University Research Field Computer science » Informatics Computer science » Programming Engineering » Computer engineering Engineering
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challenging task. In most cases, only a sample of a network is observed. Therefore, network completion needs to be addressed. Matrix completion methods have proved to be efficient when reconstructing a non
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; develop the statistical analysis plan; perform statistical analyses on the associations of air pollution and heat with asthma and lung function, using standard methods (e.g. discrete-time hazard models
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://pritykinlab.princeton.edu) develops computational methods for design and analysis of high-throughput functional genomic assays and perturbations, with a focus on multi-modal single-cell, spatial and genome editing