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Field
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programme Is the Job related to staff position within a Research Infrastructure? No Offer Description At the heart of SIT’s mission is to nurture industry-ready graduates equipped with deep technical
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modeling with deep learning for the analysis of hyperspectral imaging data. The researcher will be responsible for the design and development of numerical models, including neural network architectures
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using deep learning, computational chemistry, medicinal chemistry, chemical biology, and molecular cell biology to develop novel therapeutics to tackle complex diseases such as cancers. Successful
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operando data related to battery degradation and safety. You will develop and implement advanced deep learning models to analyse multi-modal operando data from accelerated stress testing, with the aim
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modulation, radar/sonar signal processing, and machine and deep learning. WORK PERFORMING: Individual will perform research generally in the area of statistical signal and array processing. Topics of specific
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advancing the use of computer vision, deep learning, and machine learning for analyzing medical imaging modalities such as CT, MRI, X-ray, and ultrasound. Research areas include image segmentation, detection
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electrocatalytic processes. This postdoctoral position will investigate pulse-mediated electrodeposition of metal particles using deep eutectic and organic solvents, ultimately aiming to induce kinked high-index
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partners, or translational research teams. Experience with Quarto, Python, and/or other programming languages. Experience and interest in data science or informatics education. Experience with deep learning
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learning (RL) and deep reinforcement learning (DRL) for autonomous process management, dynamic resource distribution, and real-time decision-making. Design and deploy digital twins for integrated chemical
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with deep technical expertise and transferable skills to tackle tomorrow’s challenges. SIT collaborates with industry in our education, while benefitting them with our talent supply and collaborative