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to have experience with: Phase equilibrium calculation algorithms and their integration into CO2 capture simulation Thermodynamic modeling of phase equilibrium and thermophysical properties related to CO2
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solutions and policy impacts. You will design and implement machine-learning algorithms that interact with your simulation framework for scenario discovery, building surrogate models of simulation outputs
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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contributing to developing and implementing novel algorithms at the intersection of computational physics and machine learning for the data-driven discovery of physical models. You will be working primarily with
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key responsibilities will include: Designing and implementing advanced LabVIEW and C++ based control software for our HS-DAFM platform Developing specialized signal processing algorithms and circuits
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techniques for integrating such solutions into modern SDV middleware. Responsibilities: Conduct research in runtime analysis and reconfiguration of in-vehicle TSN networks. Develop algorithms and prototypes
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statistical and machine learning techniques for dynamic energy system modelling Develop advanced optimization algorithms for building energy management and control (e.g., MPC, RL) Develop and evaluate digital
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transformative advancements in scientific discovery. Responsibilities As a Senior postdoc, you will be able to contribute to designing your own project focusing on implementing cutting-edge algorithms for graph
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research environment focusing on integrating multi-source data and developing novel algorithms to address the challenges posed by global environmental change. You will focus on integrating experiments, field