About the role

Contributing to advanced algorithms for large-scale optimization in communication networks, the full-time Research Scientist, Optimization will work remotely to develop scalable optimization algorithms, apply machine learning techniques, and collaborate with engineers to integrate research into practical applications.
Key Responsibilities: Specify, research, design, and develop scalable optimization algorithms for complex resource allocation problems Apply techniques from machine learning and optimization to enhance solution quality and computational efficiency Collaborate with researchers and engineers to translate research into commercial product capabilities
Required Qualifications: A PhD and/or 3+ years of equivalent research experience in computer science, engineering, mathematics, statistics, or a related field Strong skills in Python and experience working in Linux environments A track record of publishing in leading venues such as NeurIPS, ICLR/ICML, or INFOCOM/IEEE Experience with reinforcement learning, integer optimization, or metaheuristic algorithms Demonstrated ability to work proactively in a self-motivated manner

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