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Field
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will be part of two closely related Australian Research Council projects (Discovery and Linkage) that are using natural history collections, environmental DNA and ecological models to reconstruct
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foundational AI research in Australia, focusing on areas such as natural language processing, computer vision, and machine learning. This role offers the opportunity to carry out cutting-edge research
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properly. Please turn on JavaScript in your browser and try again. Ulla Schildt/NHM 23rd June 2025 Languages English English English The Natural History Museum Postdoctoral Fellow: Self-Developed Project
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, using an array of methods including natural language processing and experiments. This is a two-year position (one-year contract renewable based on performance). The primary criterion for acceptance is
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starting in the position approved documentation of proficiency in English (if required, cf. English language requirements for PhD admission ) a list of any works of a scientific nature (publication list
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of societal change. Our common direction is driven by consideration for green and sustainable change and equitable social development, through new ways of managing natural resources and facilitating
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, and publication list Two educational or professional recommendations. At least one recommendation must be submitted in order for the mentor to view your application. All documents must be in English or
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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language (e.g., Matlab, Python) Fluent oral and written communication skills in English (see below) Additional desired qualifications: Experience with the theoretical description of transport processes
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publication list Two educational or professional recommendations. At least one recommendation must be submitted in order for the mentor to view your application. All documents must be in English or include