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Field
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quasi-experimental methods to identify causal effects and test the predictions of economic and sociological models. Examples of current research projects include: long-term impacts of neighborhoods and
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of metrics to evaluate reconstructed data quality, compression ratio, and computational cost; Study and implementation of lossy and lossless compression techniques, including methods based on predictive coding
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optimized power management algorithms to ensure sustainable monitoring. iii) Implementation, simulation, and performance evaluation of system for landslide monitoring and prediction. Place of work: The work
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the timing of seasonal spring melt onset; and 3) Improve melt onset detection and prediction, using information from previous ROS events, using multi-frequency SAR and altimetry observations. If time allows
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) with international collaborators who will conduct experimental validation of the computational predictions to translate neuronal reprogramming into clinical practice. The Computational Biology Group aims
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Organization U.S. Department of Agriculture (USDA) Reference Code USDA-ARS-PA-2026-0338 How to Apply To submit your application, scroll to the bottom of this opportunity and click APPLY. A complete
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approaches. Develop, optimize, and maintain code and algorithms supporting predictive models. Combine computational algorithms with laboratory automation to enable self-driving laboratories and automate
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Job Code: 2026_22 Job Offer from July 30, 2026 The Max Planck Institute of Biochemistry (MPIB) in Martinsried near Munich is one of the world’s leading international research institutions in
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solutions for offshore wind turbines, enabling to enhance their structural awareness, real-time reliability assessment, and predictive maintenance decision support through integrated sensing, modelling, and
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metabolic design, supported by experimental validation, to predict, create, and expand metabolic capabilities beyond those currently found in nature. Together, these approaches aim to build a generalisable