184 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" Fellowship research jobs in Australia
Sort by
Refine Your Search
-
Listed
-
Employer
- Monash University
- Macquarie University
- AUSTRALIAN NATIONAL UNIVERSITY (ANU)
- RMIT UNIVERSITY
- University of New South Wales
- University of Sydney
- RMIT University
- The University of Queensland
- Flinders University
- MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA
- Curtin University
- University of Tasmania
- Deakin University
- FLINDERS UNIVERSITY
- James Cook University
- The University of Western Australia
- UNIVERSITY OF SYDNEY
- UNIVERSITY OF WESTERN AUSTRALIA
- CSIRO
- Charles Sturt University
- LA TROBE UNIVERSITY
- La Trobe University
- UNIVERSITY OF THE SUNSHINE COAST - UNISC
- ADELAIDE UNIVERSITY
- Australian National University
- CHARLES STURT UNIVERSITY
- Nature Careers
- QUEENSLAND UNIVERSITY OF TECHNOLOGY (QUT)
- UNIVERSITY OF MELBOURNE
- University of Melbourne
- 20 more »
- « less
-
Field
-
AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 6 days ago
machine-learning methods to investigate the deep-time controls on copper mineralisation. The role will involve developing reproducible computational workflows, generating predictive maps of copper
-
postgraduate qualification in Data Science / Computer Science (PhD preferred) Strong expertise in Python and/or R, SQL, data engineering and machine learning Experience with EMR systems (Cerner highly desirable
-
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
-
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
-
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
-
completion) in computer science, electrical engineering, AI, machine learning, remote sensing, robotics, or a closely related discipline. Demonstrated expertise and research track record in deep learning and
-
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
-
experience in using statistical and mathematical tools to analyse and interpret soil data, spatial modelling, multivariate statistics and/or machine learning, and relevant coding languages (e.g. R, Python
-
recognition for quality research outputs in the field of biological mathematics. Demonstrated mathematics and computer programming skills with experience in modelling infectious disease dynamics, population
-
relevant to integration of machine learning and mechanistic models, and development of engines for efficient processing and visualisation of large-scale datasets and system geographic information and