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Group (EASE IRTG), Empowering Digital Media (EDM), the Research Training Group HEARAZ , the Research Training Group KD²School (KD²School), π³: Parameter Identification – Analysis, Algorithms
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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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, financial reporting, and expense management. This position directs multiple teams and leaders, with an early focus on building a high-performing staff to support the University’s rapidly growing research
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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, make valuable contributions and progress in your
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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, make valuable contributions and progress in your
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Research Studentships (for students of a Master or Integrated Master students) - (BL202/2025-IST-ID)
Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 6 days ago: Until now, we have been using neural networks with traditional architectures, namely the so-called Convolutional Neural Networks (CNNs). These networks are employed as the backbone of the Multiple
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community or institutional partners. • Excellent written, verbal, and cross-cultural communication skills. • Ability to communicate in multiple languages. • Strong leadership abilities. • Ability
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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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Design and Manufacturing Engineering to Tackle Global Sanitation Challenges - MSc by Research or PhD
optimization. The research focuses on creating efficient design workflows, validating multiple additive manufacturing approaches, and developing scalable production methods that can support global deployment
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that algorithmic parameters are tuned so that the over-approximation of the computed reachable set is small enough to verify a given specification. We will demonstrate our approach not only on ARCH benchmarks, but