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of Computer Science, Norwegian University of Science and Technology (NTNU). The position offers the opportunity to work on cutting-edge research at the intersection of deep learning and computer systems. The successful
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how machine-learning-based methods can help overcome this bottleneck, opening the door to excited-state simulations at scales and system sizes that are currently out of reach. You will work at the
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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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improved using machine learning techniques. The developed techniques will be applied to metrology of semiconductor samples. Job requirements You are an enthusiastic candidates with a ‘drive’ for applied
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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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as required. To learn more about these options, please contact the NRC Hiring team using the contact information below. Build the technology behind Canadian innovation What if your next Dynamics 365
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experiments and policy-capturing methods may be used to compare interviewer judgements with evidence-based outcome measures. The project will also explore machine-learning, multimodal data analysis, computer
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, machine learning, or NLP Published work in reputable conferences or journals Outstanding academic performance in relevant modules or degrees A strong motivation to work on cutting-edge research in Agentic
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connections to their communities and you may be eligible for an exception to this work arrangement. Alternative work arrangements may also be considered to accommodate candidates as required. To learn more
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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