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that the candidate has prior research experience in one or more of the following research topics: Free space optical communication Visible light communication DSP for coherent optical communication Machine learning
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project focused on the development machine-learning powered digital twin system for the structural performance of civil engineering structures. The project is a collaboration between multiple research
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. As a Carnegie Doctoral/R2 institution, our world-class scholars instruct about 26,000 students in associate's, bachelor's, master's and doctoral level degree programs. Whether you are seeking the charm
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on reliability, security, and resilience of electric power systems and microgrids and stability analysis and Scientific Machine Learning (SciML) for microgrid applications. The successful candidate will be
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, emissions, and productivity. Decision-Support & MCDA Implement a machine-learning-driven multi-criteria decision analysis to rank and select optimal decarbonization pathways. Collaborate with industry and
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this role, we are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models
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skills and experience: Essential criteria PhD qualified in relevant subject area* Experience developing deep learning segmentation models Experience with Pytorch, MONAI, CUDA or equivalent software
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form, and attach all your materials in English in one PDF file. The file must include: Application (cover letter) CV Academic Diplomas (MSc/PhD – in English) List of publications Contact details
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You have academic qualifications at PhD level, for example within the areas of bioinformatics, machine learning or forensic odontology. We favour experience in computational data analysis, and the
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language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative ways to understanding, processing, and