Sort by
Refine Your Search
-
Listed
-
Employer
-
Field
-
3 Mar 2026 Job Information Organisation/Company UNIVERSITY OF SYDNEY Research Field Computer science Economics Mathematics Researcher Profile Recognised Researcher (R2) Established Researcher (R3
-
large-scale cross-cultural and longitudinal studies in collaboration with international research teams manage multi-site data collection, including ethical approvals and cross-country protocols conduct
-
likelihood estimators, as well as experience in estimating labour supply models and models of wage dynamics. Ability to work with large datasets, particularly panel and cross section data sets of the types
-
Scientia Professor, the Post-Doctoral Fellow will undertake advanced data management and statistical analysis of large, complex linked datasets, contribute to rigorous study design, and ensure high standards
-
must hold unrestricted work rights to be considered for this position. About Us: UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented community; a
-
strong, and ambitious research culture, with regular engagement in high-impact publications, translational projects, and large-scale funding initiatives. This integrated environment offers exceptional
-
projections. Demonstrated experience in working with large data sets. Strong programming skills (e.g. Python, R) and ideally experience in high-performance computing. Demonstrated ability to work in a team
-
developed by extending the existing platform through adoption or development of new components. Phase 2: Using big data insights to optimise the manufacturing process The second phase of this project will
-
statistical genetics techniques to analyse large-scale single-cell and genomic data. Data Analysis: Process, analyse, and interpret high-throughput single-cell and genomic data to derive biologically meaningful
-
: Using big data insights to optimise the manufacturing process The second phase of this project will focus on processing and utilising machine-learning techniques to analyse large volumes of data from