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, China [map ] Subject Areas: Physics / Atomic Molecular and Optical Physics , artificial gauge fields , Cold Atom Physics , Condensed Matter Theory , Machine Learning , Quantum Hydrodynamics , Quantum
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-quality research publications in econometrics or related fields. You will possess the ability to solve complex statistical problems, show advanced computer literacy with proficiency in relevant software
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collaboration between industry, government, and academia. The Australian Institute for Machine Learning (AIML) at the University of Adelaide is the largest computer vision and machine learning research group in
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, written, and oral communication skills in English. Exhibit strong organisational skills and the ability to meet deadlines and complete projects. Have expertise in machine learning and/or programming (highly
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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Engineering, etc.), expertise in cutting-edge AI and machine learning is essential; while structure prediction or materials chemistry experience would be advantageous, it is not a pre-requisite for the role
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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
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data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python), including a sound understanding of FAIR data principles, data management and
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to work independently and collaboratively. Advanced planning, time management, and written communication skills are essential, along with proven computer literacy and proficiency in relevant software and
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to apply advanced AI models in areas such as catalyst design, multi-scale modeling, and spectroscopic analysis. The Research Fellow will take on a significant role in machine learning theoretical energy