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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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controlled. A central objective is to develop measurement-based methodologies that establish the relationship between manufacturing precision, process capability, and product quality. Precision metrology and
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aims to develop new knowledge about how AR can support work in underground mines. The project aims to develop and implement Augmented Reality (AR)-based maintenance support for drill rigs. Its objective
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investigator, other postdocs, PhD students, and external collaborators to advance research objectives and generate high-impact results. In addition to research, some participation in supervision of doctoral
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industry and includes practical process work, sample handling, analysis and interpretation of results in relation to the project objectives. Detailed description of the work duties, such as: plan, conduct
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and plasmonic nanoparticles. You will contribute to both technical development and fundamental research. This may include improving parallelized optical detection, integrating optical tweezers with
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in relation to the project objectives. Detailed description of the work duties, such as: plan, conduct and document laboratory- and pilot-scale experiments in dairy and membrane processes, develop and
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, knowledge-driven models and AI-based decision support can be integrated to support resilient and energy-aware manufacturing systems. Special emphasis will be placed on multi-objective optimization, learning
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crystals of inorganic molecular solids, extend the materials family and find better synthesis routes to it. Lead experiments in advanced materials characterization, including variable-temperature diffraction
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as a critical design metric. Key research objectives include: Mixed-precision algorithms: Designing and implementing mixed-precision formulations for key domain-specific kernels to leverage low