39 learning-"https:"-"https:"-"https:"-"https:"-"https:" "Inria" Postdoctoral research jobs in Australia
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Primary supervisor Chern Hong Lim Co-supervisors Bisan Alsalibi Yasmeen George Research area Data Science and Artificial Intelligence While deep learning has shown remarkable performance in medical
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ultimately shifts in species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species
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the interview stage. A two-year fixed term, full time (37.5 hours per week) position. View the full Position Description for this position at: https://careers.sciencenewzealand.org/niwa/about-us
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University job portal before the closing date. (Monday 5 October 2026, 11:55 pm AEDT) Apply here: https://careers.pageuppeople.com/513/cw/en/job/690226/postdoctoral-research-fellow-computational
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 16 days ago
opportunities to those of all backgrounds and identities. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion Application information
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 26 days ago
all backgrounds and identities. For more information about staff equity at ANU, visit https://services.anu.edu.au/human-resources/respect-inclusion Application information In order to apply for this
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consult their website for collective agreement https://www.aerum-amure.ca McGill University is strongly committed to diversity within its community and especially welcomes applications from racialized
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effectively within a multidisciplinary research environment. Experience with quantitative genetics, Bayesian methods, machine learning, large-scale genomic datasets, single-cell omics or integrative
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cutting-edge bioinformatics, AI, machine learning, and multi-omics technologies to drive discoveries that have the potential to transform cancer diagnosis, treatment, and patient outcomes. This is an
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using Python, ASE and relevant DFT software analyse electrochemical free-energy landscapes and connect elementary-step energetics to catalytic performance apply machine-learning interatomic potentials and