Postdoctoral Fellow Deep Reinforcement Learning
Performance and Learning
Develop graph-based inverse reinforcement learning and deep learning models as a Postdoctoral Fellow with the NRC in Hamilton. Work full-time onsite.The National Research Council seeks a Postdoctoral Fellow for a two-year term in Automotive and Surface Transportation. You will analyze driver eye-gaze scanpaths under adverse weather, infer reward structures, and forecast gaze trajectories and driving actions. The work supports innovative research within a multidisciplinary team and includes participation in additional projects.Key Responsibilities:
Develop graph-based inverse reinforcement learning frameworksAnalyze and forecast human driver eye-gaze scanpathsApply spectral graph analysis to gaze patternsBuild deep learning prediction pipelinesParticipate in multidisciplinary research projectsRequirements:
PhD in Computer Engineering, Computer Science, or related fieldTwo to six years developing advanced deep learning architecturesClear, concise Python or C++ coding experienceExperience with PyTorch, TensorFlow, and machine learning librariesEnglish language proficiency and Reliability Status eligibilityApply deep learning, graph analysis, and reinforcement learning expertise to driver attention research at the NRC.
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Develop graph-based inverse reinforcement learning frameworksAnalyze and forecast human driver eye-gaze scanpathsApply spectral graph analysis to gaze patternsBuild deep learning prediction pipelinesParticipate in multidisciplinary research projectsRequirements:
PhD in Computer Engineering, Computer Science, or related fieldTwo to six years developing advanced deep learning architecturesClear, concise Python or C++ coding experienceExperience with PyTorch, TensorFlow, and machine learning librariesEnglish language proficiency and Reliability Status eligibilityApply deep learning, graph analysis, and reinforcement learning expertise to driver attention research at the NRC.
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Vacancy posted 1 hour ago
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