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Field
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1. A PhD degree in a relevant area, e.g., Chemical Engineering, Control Engineering, Computer Science, Systems Engineering, etc. 2. The candidates should have strong math, modeling, programming, and
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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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and machine learning algorithms to analyse and interpret the acquired data. The successful candidate will work primarily with Dr Qimei Zhang in the Department of Engineering at the Nottingham Trent
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• Possess a PhD in a related discipline (transportation engineering, operations research, computer engineering/science, or related disciplines) by December 2024. • Strong knowledge and
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The successful candidate should possess the following: • A PhD in Materials Science, Chemical Engineering, Chemistry, Physics, or related fields • Highly motivated, committed, and capable
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, fabrication materials and orbital environments. Using a small number of representative test cases, we will trial Machine Learning-based predictive methods to estimate material condition and indicative reuse
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lab experiments Publish results in top-tier journals in related fields Assist in mentoring PhD students Job Requirements: PhD degree in mathematics, systems engineering, or machine learning Expertise in
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privacy, machine learning, and applied cryptography. To produce research papers and reports as required by the funding body or for dissemination to the wider academic community. To provide guidance and
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-UAS technologies o Multi-agent systems and swarm robotics o Autonomous navigation and guidance o Computer vision and perception o Machine learning
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to technology development, knowledge dissemination, and translational opportunities Job Requirements: B.S in Chemistry with a focus on computational/peptide/organic/machine learning or a closely related