167 molecular-modeling-or-molecular-dynamic-simulation-"Multiple" PhD positions in Australia
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, leveraging existing literature and data from controlled experiments. The model will consider multiple photosynthesis parameters to predict microalgae growth. It will offer specific design criteria and
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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children. Mechanistic modelling of disease transmission involves the use of computer code to represent the epidemic dynamics of infectious disease spread within the community. This allows modellers
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to integrate floating offshore wind turbines and wave energy converters to capture wind and wave energy. The hybrid system’s dynamic responses will be investigated and advanced vibration control technologies
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prediction, signal tracking, fluid dynamics, and space exploration. Advancing Signal Modelling with Physics-Informed Neural Networks This project aims to develop Physics Informed Neural Networks (PINNs
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need: A PhD in Molecular Biology, Cell Biology, Genetics, Biotechnology, or a related area. Expertise and interest in cancer and/or stem cell biology and associated techniques. Outstanding academic track
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the structure and function of chromatin-associated complexes involved in gene repression. About Us: We are a dynamic and international team working within the South Australian immunoGENomics Cancer Institute
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need: A PhD in Molecular Biology, Cell Biology, Genetics, Biotechnology, or a related area. Expertise and interest in cancer and/or stem cell biology and associated techniques. Outstanding academic track
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underwater communications is necessary. Conventional approaches in underwater communications only develop fixed models based on human knowledge or understanding which cannot fully cover the highly dynamic and
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materials systems at the molecular level with machine learning. The PhD Student will undertake a study analysing mass spectral imaging data streams in real time using machine learning workflows. A pathway for