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We are looking for a motivated summer intern to join a collaborative project aimed at improving the performance of superconducting qubits by optimizing noise filtering in dilution‑refrigerator
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Council (VR). The project is centered around inverse optimal control/inverse reinforcement learning, both for continuous-time and discrete-time systems. In particular, we are looking for a strong candidate
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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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. The candidates will be working with the QV2 software team and will learn to develop scientific software in a collaborative environment. Project 1: Readout Optimization and Software Development This project focuses
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Do you want to contribute to groundbreaking research in the intersection of battery systems and data-driven optimization? This is an exciting opportunity for a postdoctoral position at the Division
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implemented globally. The research includes optimization of the electrochemical processes for mercury removal as well as safe and efficient retrieval of the removed mercury and regeneration of electrodes
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treatment and hot isostatic cracking) to minimize/avoid cracking and optimize microstructure and properties. You will be working with hands-on manufacturing, microstructure characterization using advanced
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for industrial application. You will develop materials and processes enabling this technique to be scaled up and implemented globally. The research includes optimization of the electrochemical processes
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plan (e.g., microfluidic channel optimization, polarization-dependent scattering studies, spectral imaging implementation, or algorithm development). Planning experimental campaigns, simulations, and
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., microfluidic channel optimization, polarization-dependent scattering studies, spectral imaging implementation, or algorithm development). Planning experimental campaigns, simulations, and modeling efforts