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qualifications: Ph.D. in Forest Resources Experience working with lidar data and appropriate algorithms Experience with GIS and remote sensing Knowledge of natural resource science as it applies to forestry Pay
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-doctoral Associate will develop algorithms and theory for machine learning methods, as well as implement and apply ML methods to problems in domains such as computational biology and neuroscience. This is a
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clinical observerships in a graduate engineering program Proficiency in algorithm design leveraging linear algebraic methods Proven experience applying LEAN methodologies to rapid prototyping in medical
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across time and contexts. Job Description: You will develop and apply mathematical models and machine learning algorithms to analyze the structure and evolution of knowledge systems across different
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Localization and Mapping) algorithms, integrating data from sources like GPS, IMU, and LiDAR to achieve robust vehicle localization. Implement, test, and tune navigation controllers (primarily the visual
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and verification, domain-specific computing, heterogeneous architectures, hardware-algorithm co-design, quantum, and physics-inspired computing. AI: Expertise in algorithms, theory, and applications
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of computer algorithms/code related to simulations, data analysis, visualization and dissemination in support of space physics research. Job Duties 65% Implementing, testing, editing and running simulation
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outcomes. The individual will be expected to develop stimulation strategies and testing algorithms, write code, and develop software. They will do extensive validation and testing, under the supervision
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of research projects in a variety of domains. Under the onslaught of ever-larger amounts of data and to take advantage of improvements in machine algorithms, the Zooniverse team has built and implemented
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validate signal processing algorithms and stimulation strategies using electrophysiological and behavioral data. Develop GUIs, psychophysical test protocols, and objective outcome measures (e.g., ECAP, ABR