Sort by
Refine Your Search
-
, using Jax, PyTorch, and/or Julia, or similar tools Essential criteria A Doctorate in a relevant field such as Astrophysics, statistics, or applied mathematics, with a strong background in astronomy
-
proficiency in Python and R for scientific computing and pipeline development demonstrated experience in quantitative, statistical or data-driven modelling of biological systems experience developing
-
inference in physics contexts. Essential criteria A Doctorate in a relevant field such as Astrophysics, statistics, or applied mathematics, with a background in astronomy Experience in both statistics and/or
-
or contributing to in vivo studies, including delivery, tissue collection, and phenotyping ability to analyse and integrate experimental datasets using Python or R, including scripting, statistical analysis, and
-
or contributing to in vivo studies, including delivery, tissue collection, and phenotyping ability to analyse and integrate experimental datasets using Python or R, including scripting, statistical analysis, and
-
Econometrics (particularly applied micro, behavioural, or decision-focused modelling) Applied Mathematics, Operations Research, or Statistics Systems Engineering, Decision Science, or Complex Systems
-
, Operations Research, or Statistics Systems Engineering, Decision Science, or Complex Systems. demonstrated research capability in one or more of the following areas: quantitative modelling of dynamic
-
health concerns and alcohol/drug use harms to optimize prevention, early intervention, and treatment approaches; Lead preparation of research outputs, including conducting statistical analyses and
-
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
-
, Operations Research, or Statistics Systems Engineering, Decision Science, or Complex Systems. demonstrated research capability in one or more of the following areas: quantitative modelling of dynamic