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, band selection Heterogeneous network architectures, including terrestrial and non-terrestrial networks Deep learning for wireless communication problems, particularly in areas such as spectrum management
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inequalities Markov processes and stochastic analysis Theoretical analysis of neural networks and deep learning Foundations of reinforcement learning and bandit algorithms Mathematical and algorithmic
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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field. Experience in one or more ML domains, such as deep learning, reinforcement
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apply. A PhD dissertation or research papers that demonstrate a strong interest and research focus in any of risk analysis or minimization, robust optimization, deep learning for systems, probabilistic