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with FPGA programming used in superconducting quantum circuit experiments. Model-Free Quantum Control via Reinforcement Learning: Reinforcement learning (RL) is an emerging approach for optimizing
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welcome from all areas of operations research, including but not limited to optimization, mathematical programming, analytics, data-driven decision-making, stochastic modelling, and systems analysis. We
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project, you will help design, simulate, and optimize these next-generation communities — making clean, local, and intelligent energy systems a practical reality. Your key responsibilities include
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computational tools, including optimal-control techniques, that directly support ongoing experiments and advance the control of bosonic quantum operations. About us The position is hosted at the Applied Quantum
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a member of a team in a collaborative environment. Strong mathematical and analytical skills. Strong technical background in optimization in wireless communications/networking. Experience with
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14 Feb 2026 Job Information Organisation/Company Empa Research Field Computer science » Other Engineering » Other Mathematics » Applied mathematics Technology » Energy technology Technology
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9 Feb 2026 Job Information Organisation/Company CNRS Department Sciences et Ingénierie, Matériaux, Procédés Research Field Computer science Mathematics » Algorithms Researcher Profile First Stage
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, and written communication skills evidenced by a publication record in the area of control theory, mathematical optimization, AI, or machine learning. Preferred Qualifications: Publication record in
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options and persuasively advocate for optimal technical solutions, internally and externally. Responsible for responding, triaging, and resolving production system issues in a timely fashion, across
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mathematics Application deadline: February 23, 2026 Doctoral student in Geometric Hydrodynamics Application deadline: February 23, 2026 Doctoral student in discrete optimization and computational complexity