20 coding-"https:"-"Prof"-"FEMTO-ST"-"https:"-"https:"-"https:" Fellowship positions in Australia
Sort by
Refine Your Search
-
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
-
/partners on the project. Align with and actively demonstrate the Code of Conduct and Values. Cooperate with all health and safety policies and procedures of the university and take all reasonable care
-
suitability checks: In accordance with the National Higher Education Code to Prevent and Respond to Gender-based Violence, appointment to this role is subject to successful completion of relevant pre-employment
-
to support translational outcomes and shared priorities perform quantitative and qualitative data collection, coding, analysis and interpretation, and contribute to the production of high‑quality peer‑reviewed
-
funding Knowledge on a coding language (Phyton, etc) The successful candidate may be required to complete a number of pre-employment checks, including: right to work in Australia, conduct concerning gender
-
and optimise code and digital-twinning platforms with industry partners, produce high-quality research outputs and reports, contribute to funding applications, and deliver training workshops and
-
citizenship behaviours align with the ARC-IFC’s Code of Conduct and UQ values. Build and maintain strong relationships with Indigenous communities and ARC-IFC’s community partners and other end-users
-
(e.g., LabArchives, BioRender). Desirable Demonstrated experience in fermentation control, optimisation and scale-up. Experience in the use of electronic lab books Experience in coding languages (Python
-
the Code of Conduct and Values. Cooperate with all health and safety policies and procedures of the university and take all reasonable care to ensure that your actions or omissions do not impact on
-
results. High levels of personal integrity, transparency and capability. Experience in crop model coding is desirable. Experience in statistical analysis and data visualisation (e.g. R, Python) is desirable