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-constrained devices such as wearables, smart sensors, hearables, and IoT nodes. While current deployment methodologies can optimize models before deployment, the resulting software remains static throughout
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and its impact on pasteurization, fermentation, coagulation, and shelf-life. Controlled processing trials generate datasets to model processing performance enabling model based optimization. PhD1 (KU
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/data-driven modelling; parameter identification and optimization; scientific software development. Importantly, direct experience with PVD is not mandatory. Candidates with strong backgrounds in
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more sustainably. While business processes are traditionally optimized for efficiency, cost, and quality, organizations are now expected to actively manage their environmental footprint and social impact
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to evolve alongside changing technologies and business needs remain equally important. Your responsibilities As an ICT Data Engineer, you will: Engineering & building data solutions Develop and optimize
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this project, you will develop the next generation of robot VLA and world models. By combining optimizations such as quantization, pruning and distillation, we aim to build models that can be deployed on real
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of gene therapy manufacturing and process innovation. The project focuses on the development and optimization of scalable bioprocesses for viral vector production and downstream purification and
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transition. This ambitious goal will be achieved by developing advanced experimental and computational tools to characterize e-fuel combustion processes, optimize fuel-flexible technologies, and integrate
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CO2 reduction at elevated temperature and pressure and incorporate them in a transport-optimized electrolyzer of your own design. The aim is to unravel the combined impact of temperature and pressure
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deploying the face de‑identification pipeline on resource‑constrained hardware, optimizing the underlying AI models based on latency, memory, and power constraints, and building demonstrators that showcase