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-platforms-lab . About You (Selection Criteria) You are a motivated and collaborative early career researcher with a strong foundation in AI and machine learning, and a genuine enthusiasm for applying
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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in
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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in
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the key focus areas: Emerging track record and recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in
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/empirical analysis Technical capability in behavioural and organisational cyber security, and desirable experience applying AI or machine learning to cyber security contexts. Proven publishing ability across
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systems (such as RedCAP), Endnote files, and databases Demonstrated experience with data analysis, visualization, and building machine learning models in programming language such as Python or/and R
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Innovations Group seeks a forward‑thinking expert in statistical machine learning to translate complex biological datasets into actionable AI‑driven insights. You will enhance genomic selection and breeding
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
processing, computer programming, and fieldwork are encouraged to apply. The successful candidate will be a member of the Geophysics Department based at RSES. RSES is Australia’s leading academic research
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developing research projects and reporting against milestones. Experience working with a range of computer systems and applications, including referencing software (e.g. EndNote), survey platforms and high
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Earth Engine, ENVI, MATLAB, or R. Desirable Proficiency in applying machine learning methods to multispectral and hyperspectral data for detecting crop diseases and estimating crop yield and quality