Sort by
Refine Your Search
-
: Experience in physical system modelling including finite element modelling Experience working with large codebases in open source software environments Proficient user of HPC environments including MPI
-
Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
to modulate protein translation. This project will use RNA cross-linking technology to understand all of the RNA-mediated control elements that contribute to the system of regulation that links metabolic needs
-
overall, with no less than 6.0 in each component How to apply For general instructions on how to apply for roles at Monash, please refer to 'How to apply for Monash Jobs '. To express your interest in
-
PhD student(s) will join a vibrant team of postdocs, academics, and up to four PhD students working collaboratively across modelling, qualitative fieldwork, and optimisation techniques. PhD Research
-
the structure present in food systems dictates functional aspects such as digestion and release of nutrients. Working alongside other postdocs and students focused more on biological aspects of these processes
-
who hold an Australian (or equivalent international) Honour’s or Master’s degree (both in a relevant field), with a significant research component and with first-class honours/H1 awarded. Details
-
software such as redcap, R, python. Experience in clinical trial management and coordination, including regulating clinical research with a large human subjects component. Strong knowledge of ICH Guidelines
-
PhD Scholarship in Digital Mapping of Homemade & DIY Cultural Economies in First Nations Communities
, the selection committee will prioritise First Nations applicants who hold an Australian (or equivalent international) Honours or Master’s degree (both in a relevant field), with a significant research component
-
Dowe, 1999a) ensures that - at least in principle, given enough search time - MML can infer any underlying computable model in a data-set. A consequence of this is that we can (e.g.) put latent factor
-
such systems are limited to the learning errors due to the neural component. In this Ph.D. project, you will be exploring the use of Lipschitz Continuous Neural Networks to learn Lipschitz-bounded neural models