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an opportunity for a Postdoctoral Fellow. You will contribute to UNSW’s research efforts in developing machine learning and deep learning algorithms for dynamic systems (sequential or time-series data). Experience
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temperature, flux rate, surface coverage, plasma composition and excitations. The seeding process of a new layer in heteroepitaxy requires large-scale surface modelling with accurate force-field parameters
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metapopulation and/or individual based models Knowledge of Bayesian methods, including Approximate Bayesian Computation Experience with big data analysis and HPC environments Knowledge of additional programming
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& upskilling opportunities . For more information on a range of lifestyle, financial and non-financial rewards and programs, please click here . To see what the Science and Medicine at ANU community is like, we
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experience using Python machine learning and large language models. Experience in machine learning and NLP for automated misinformation detection, social media data scraping and analysis, and human annotation
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projects including complex data analysis (e.g., telemetry or genetic data) and paper writing The candidate will be working remotely (i.e. off-campus) providing excellent work flexibility Position Overview
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Research here and the Burr Lab here: www.burrlab.com For more information about the position please contact A/Prof Marian Burr at E: Marian.Burr@anu.edu.au Working at ANU This is an opportunity to work with
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, Designated parent rooms, quiet spaces and childcare facilities on campus, Career support, training, mentoring & upskilling opportunities. For more information on a range of lifestyle, financial and non
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HDR students A history of successful competitive grant applications. Editorial experience in managing a large edited collection or equivalent. As this is a fixed-term contract, you will require current
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using statistical analysis. Experience in project management and working on field projects in the parenting field, and/or experience in working on large scale projects using administrative data. Relevant