34 high-performance-computing-postdoc Fellowship positions at Monash University in Australia
Sort by
Refine Your Search
-
Research Fellow - Environmental Informatics Hub Job No.: 680160 Location: Clayton campus Employment Type: Full-time Duration: 2 year fixed-term appointment (with the possibility of an additional 2
-
. Your expertise includes machine learning techniques such as Bayesian optimisation, and you’re comfortable working with experimental data, high-performance computing environments, and (ideally) thin film
-
for Health Economics is seeking a Level A Research Fellow to play a key role in an ongoing research program examining the effectiveness and cost-effectiveness of behavioural interventions, with a particular
-
, and may utilise iterative algorithms, machine learning and high-performance computing. Through the Monash Centre for Electron Microscopy, opportunities exist to acquire large experimental datasets using
-
performance of novel concrete Contribute to high-impact, multidisciplinary research Support environmental sustainability outcomes This is a great opportunity to develop your research expertise and contribute
-
Architecture is seeking to appoint a Level A or Level B Post-Doctoral Research Fellow to contribute to a high-impact, interdisciplinary research initiative. This role is designed to advance a collaborative
-
, to undertake further research leading to high-quality publications and conference outputs.The position involves active participation in academic events, limited administrative duties, occasional teaching
-
the Addiction & Impulsivity Research Lab and the Computational & Systems Neuroscience Lab . You will be part of a collaborative environment that integrates expertise in psychology, neuroscience and computational
-
in the vibrant world of Indonesian history at Monash University's Faculty of Arts. Join one of Australia's most dynamic arts faculties, renowned for its strengths in humanities, performing arts
-
an interdisciplinary, purpose-driven team. You have: A postgraduate qualification in Computer Science, Data Science or related field Extensive experience working with large-scale, high-frequency (waveform) data