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Field
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environmental data Processing and analyzing large-scale remote sensing datasets from UAV, satellite, and ground-based sensors Leveraging artificial intelligence, e.g. machine learning, reinforcement learning
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Responsibilities Development of new machine learning modeling approaches Development of new advanced control and optimization algorithms Optimization of carbon capture process operation Provide regular project
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AI/machine learning, and data analysis using MATLAB or Python. Provide technical assistance on related research projects, such as preparing progress presentations and reports for funding agencies
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computer programming to verify the efficiency of the designed solution algorithms Analyze data acquired from the field survey Develop machine learning models for prediction and recommendation Job
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Methodology The PhD candidate will develop innovative AI models using machine learning and deep learning frameworks. Methodologies will include supervised and unsupervised learning approaches to identify and
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Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning approaches
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at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT’s Materials Modelling and Simulation group to apply classical Molecular Dynamics and Machine Learning
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, cybersecurity, computer networking, machine learning, AI, ERP and cloud computing Conduct research with colleagues. Strong data analytics skills, including the ability to work with large sets of structured and
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Responsibilities: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety
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integration Key areas: § Metagenomic and 16S rRNA sequencing analysis § Single-cell RNA-seq and proteomic/metabolomic data integration § Machine learning and AI applications in microbiome data