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numerical solvers for 2D and 3D phase field models Develop HPC-ready simulation pipelines for large-scale rupture and fracture-fluid systems Optimize performance for modern architectures including GPUs and
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specialized differentiable numerical solvers for trajectory optimization that generate informed motion trajectories for contact-rich manipulation tasks, handling complex dynamics and physical constraints
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 15 hours ago
development and lifelong learning and enjoy exclusive perks for numerous retail, restaurant and performing arts discounts, savings on local child care centers and special rates on select campus events. UNC
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. The key responsibilities of this position include: Perform numerical simulation to solve fluid-solid-interaction problems Perform design optimization, especially AI-based generative design Master domain
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solid particle transport. The successful candidate will contribute to the creation of an AI-optimized platform capable of achieving up to 50× speedups in simulation performance, enabling real-time, energy
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, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and/or Python are required. These should be documented, for example through a
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one of the following areas is required: Numerical methods for large-scale, ill-posed nonlinear inverse problems Numerical optimization techniques Machine learning Strong programming skills in Matlab and
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, policy, energy conversion, new business models, techno-economic and life cycle analyses, machine learning, optimization, AI, intelligent networks, among others. The PDF will join a project in collaboration
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-generation sequencing assay for clinical use (LDT) and developing and optimizing methods to conduct assay manufacturing in house or in a mobile setting under ISO conditions for clinical use. Where will I be
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) and economics (or related fields). Applicants must have experience in one or more of the topics: Model-predictive control Numerical optimization Econometrics Virtual power plants Power systems and/or