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, graduate students, industrial collaborators and specialists in optimization, data science, AI/ML and emerging computing technologies across Purdue and with advanced computing platforms (D-Wave, IBM-Q, etc
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computing. Design and develop algorithms for for cache management and job scheduling in modern computing systems (such as LLMs). Analyze theoretical aspects of distributed systems, including optimization
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computing. Design and develop algorithms for for cache management and job scheduling in modern computing systems (such as LLMs). Analyze theoretical aspects of distributed systems, including optimization
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Mathematical foundation, particularly in linear algebra, probability, and optimization Background or strong interest in quantum computing, quantum information, or quantum algorithms Knowledge of machine
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Mathematical foundation, particularly in linear algebra, probability, and optimization Background or strong interest in quantum computing, quantum information, or quantum algorithms Knowledge of machine
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or distributed computing, algorithm design and analysis, and optimization Relevant research experience with proven records. Independent, highly analytical, proactive and a team player Excellent
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Job Description Job Alerts Link Apply now Senior Research Fellow, School of Computing University-Level Unit: School of Computing Faculty/Department-Level Unit: Department of Computer Science Employee
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– mathematical, computing, and simulation frameworks required to implement and evaluate the performance of optimization algorithms and solutions. Creatively identify new opportunities to leverage AI
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optimization, intelligent runtime systems, code generation and transformation, HPC, parallel and distributed computing, compiler infrastructures, heterogeneous systems, and autonomous system optimization
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design spaces. In this role, you will lead a research program centered on AI-driven autonomous synthesis, including: Active learning and Bayesian optimization over synthesis parameters such as