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in securing external research funding. You will harness your energy sector networks to explore new research and funding opportunities.You will demonstrate strong expertise in managing complex projects
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: Developing and deploying machine learning models (e.g. graph neural networks, neural force fields, diffusion models) for molecular property prediction and molecular generation. Integrating quantum chemistry
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six globally networked campuses and international alliances across Asia and Europe. The applicant will be based at the Clayton campus in Melbourne and will have access to international mobility grants
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Digital literary studies Monash University is the largest university in Australia and regularly ranks in the top 100 universities worldwide. Monash has six globally networked campuses and international
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processing, or autonomous driving. Proficient coding skills in Python, preferably with hands-on experience on deep learning frameworks such as PyTorch, TensorFlow, or Keras. Project funding Project based
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Multiple PhD Scholarships available - Cutting-edge research at the frontiers of Whole Cell Modelling
movements across the cell envelope, to help inform mathematical models that integrate all of the envelope’s function. Uncovering RNA-RNA Networks in the Regulation of Bacterial Surface Proteins: Bacterial
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Certificate (UEC) schools network in Malaysia. It underscores our commitment to seek out, reward and support students who want to change the world for the better. Applications No application required Total
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experience and networks in Indonesia are highly regarded. The role will commence in January 2026. Why Join Us Lead a globally influential, multidisciplinary centre with impact across Australia and Southeast
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In collaboration with people from Monash materials engineering, neuroscience and biochemistry we are developing living AI networks where neurons in a dish are grown to form biological neural
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with real-world application to pressing health challenges. In this role, you will: Develop new statistical methodology to support adaptive variants of cluster randomised trials Write R or Stata code