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Field
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discipline. A strong curiosity for human gait and neuromuscular control after stroke. Experience with wearable-sensor (IMU) data and human motion analysis. Solid programming skills (ideally, in Python
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discipline. A strong curiosity for human movement analysis and markerless motion capture. Experience with pose estimation, computer vision, and/or synthetic data generation for model training. Solid
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. Essential qualifications PhD in computational statistics, bioinformatics, systems biology, or a related field. Strong expertise in statistical methods, including machine learning approaches, for analysis
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of/on networks with higher-order interactions. This will be in collaboration with an NSF-funded ASU-UCLA team using ants as a model system and developing theory to characterize dynamic processes on networks as
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carcasses for analysis. Your task will be to explore what we can learn from the beached bird data. Topics include the distribution of mortality in time and space, and among species; causes of death, as
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Integrating cross-disciplinary research related to the storyline from several work packages, research groups and institutions of NCCR CLIM+, ranging from natural climate models to the analysis of impacts
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of hybrid quantum-classical modelling approaches that support improved analysis, simulation, optimisation, and decision making under uncertainty. The role will suit a researcher with strong technical
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decisions. Adheres to University and unit-level policies and procedures and safeguards University assets. Develop various machine learning and data mining models including deep convolutional neural networks
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wearable-sensor (IMU) data and human motion analysis. Solid programming skills (ideally, in Python) for algorithm development, control design, and data analysis. Confidence and interest in testing and
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Engineering, Biomedical Engineering, Computer Vision, Robotics, or a related discipline. A strong curiosity for human movement analysis and markerless motion capture. Experience with pose estimation, computer