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Field
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will work at the interface of first-principles theory (e.g., DFT) and reactive force field modeling (e.g., ReaxFF), developing multiscale, high-throughput workflows that simulate and optimize growth
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such as organic precursors and tailored growth conditions designed to optimize material properties. Understanding these complexities requires a deep dive into the atomistic mechanisms at play, where
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for an in-house X-ray beamline for long-term operando investigation of chemical hydrogen storage reactors Modeling and simulation of the beamline to analyze and optimize system behavior before physical
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Your Job: Develop techniques to simulate, control, and optimize the time-dependent dynamics for increasing system complexities Implement and optimize small quantum circuits on super- and semi
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manufactured at Uppsala University) will be the focus of this PhD project. The objectives of this work are to optimize an experimental setup for simultaneous tension/compression testing and localized corrosion
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faults that affect their performance and energy consumption. Effective and timely fault detection is essential to maintain optimal operation and reduce downtime. In this context, the application
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, multiparametric flow-cytometry and single-cell transcriptomics to identify and optimize highly innovative antiviral vaccine concepts in collaboration with leading international laboratories. The department of Viral
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printer driver Cuttlefish which prepares data for 3D printing to achieve the optimal color reproduction. In addition, we develop data-driven design software to establish a digital process with additive
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evaluation, parameter updates, and likelihood computation. Optimize the implementation for high-dimensional datasets using PyTorch, with attention to numerical stability and efficiency. Develop unit tests and
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Gaussian Mixture Model (GMM) learning Contribute to implementation, optimization, and benchmarking tasks in GPU-accelerated environments Assist in preparing experimental results and documentation