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knowledge, innovations, and solutions that help move the world forward. Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to
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multilingual settings, such as machine translation, and emerging agentic and interactive multimodal NLP systems involving human-AI collaboration present frontier evaluation challenges. The ultimate goal is to
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, physiology and disease development; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting
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Engineering, Machine Learning, Applied Mathematics, or a related field. A strong academic background and interest in AI systems, embedded intelligence, edge computing, machine learning, or related areas. Strong
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will then develop XR applications that provide real-time guidance through visual, auditory, or haptic feedback in everyday situations. Using wearable devices, machine learning, and cognitive models you
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of inverse photonic design, machine-learning (adjoint or topology optimization), or other advancing design methodologies. Ability to design and model active photonic devices (MEMS, electro-optic or thermo
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paradigms that support collaborative processes rather than isolated individual use. Combining perspectives from the learning sciences, Computer-Supported Collaborative Learning (CSCL), Computer-Supported
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will then develop XR applications that provide real-time guidance through visual, auditory, or haptic feedback in everyday situations. Using wearable devices, machine learning, and cognitive models you
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be used to combine these datasets while accounting for their different spatial scales, uncertainties and sampling frequencies. Machine-learning methods may also be explored for retrieval, bias
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various relevant computer software applications. • Assist with literature research, editing and preparing manuscripts, scientific illustrations and computer graphics for publication. • May perform