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Field
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may include integrated adversarial detection, conformal prediction, and prompt filtering. Techniques relevant to safety and resiliency in autonomous vehicles may include optimal control, differential
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of neuroimaging data to predict subjective experiences and individual differences, as well as cognitive modeling of decision-making in both lab and realworld settings. Successful candidates will be supported in
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 3 days ago
Data Exchange Standard (ADES); (2) modernizing short-term impact monitoring through adaptive search algorithms for systematic ranging (Scout); and (3) refining long-term impact prediction via improved
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networks are controlled, to develop predictive models of methane cycling in northern rivers. This postdoc position will focus on assessing how stream methane emissions are linked to permafrost thaw, using
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, and to develop predictive models that can guide the rational design of next-generation BioAg products tailored for diverse agricultural systems around the world. Responsibilities The postdoc position
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based on performance and available support. Environment and Opportunities The lab focuses on developing AI methods to improve patient diagnosis, prognosis, treatment response prediction, and treatment
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research. The Postdoctoral Scholar – Pharmacometrics in the PhASR will support data collection, quality control of data, data analysis, modeling, simulation and PK/PD study design for human clinical trials
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | about 2 hours ago
is reproduced in the NASA Ames Electric Arc Shock Tube (EAST) facility, and is used to test models developed to predict the heating mechanisms. The primary models employed are the DPLR computational
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health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim
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modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process