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, personalized (re)routing, i.e., generating routes and offering route suggestions based on mobility behavior, travel conditions, trip characteristics, and user preferences. Defined routes trade-off multiple
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electricity price signals, demand-response mechanisms, and time-of-use optimization. AI-Driven Optimization using Reinforcement Learning: Apply RL algorithms to develop and train agents that optimize power
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software frameworks, algorithms, robust testing and validation methods, and/or empirically validated solutions that contribute directly to social good, promoting trust, fairness, transparency, and
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conditions, trip characteristics, and user preferences. Defined routes trade-off multiple criteria, where the exact importance of each objective is user dependent, and can be learned and improved over time
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National Research Council Canada | National Capital Region Almonte, Ontario | Canada | about 7 hours ago
at all levels. We value teamwork. You’ll collaborate across multiple fields and with the brightest minds to find creative solutions. Most importantly, you’ll discover what’s possible within you as you grow
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experience mentoring graduate students and contributing to the development of grant proposals • Research background spanning multiple emerging areas such as AI/ML for communication systems, age of information
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practices. Qualifications: A PhD in the Social Sciences or the Humanities. Strong research and writing skills, demonstrated in the publication of multiple peer reviewed journal articles. Deep familiarity with
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· Gender-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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in a structured doctoral training environment. The need of microbiome research in the current age lies in joining forces from multiple disciplines to focus on understanding causal and mechanistic links