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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | about 1 month ago
research methods. The ideal candidate will have expertise in experimental and survey research design, advanced statistical analysis (e.g., multi-level modelling, mediation/moderation analysis, longitudinal
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expertise in cancer cell metabolism and blood cancers. Ideal candidates will have experience in genetic mouse models, cytometry, cell culture, and metabolic analyses. The project uniquely provides
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cancer stem cells using human primary tumor xenograft and transgenic mouse brain tumor models. This research will be a collaborative effort among the Department of Neurosurgery, Cell and Developmental
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: simulation and risk modelling using advanced statistical and machine learning based methods. strategic portfolio management and dependency structure modelling for financial assets. effects of climate change
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internal institution systems may be submitted. Click here for detailed information about acceptable transcripts. A current resume/CV, including academic history, employment history, relevant experiences
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droplet tunnel, supported by fundamental modelling of molecular dynamics and ice/substrate interactions. The Research Fellow will conduct icing experiments in the Cranfield Icing Wind Tunnel, support test
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should include: A Ph.D. degree in life or biomedical sciences, or related discipline is required. Experience with mouse (PDX, humanized) models. Ability to effectively lead other scientists in a
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Applications are invited for a part-time Research Fellow position until August 2026 (with possible further extension). The role will encompass activities related to the financial modelling of zero
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. For the Laboratory for Waste Management – Transport Mechanics group and within the scope of a research project funded by SwissNuclear we are looking for a Postdoctoral Fellow in AI-enhanced modelling of boiling
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position (100%, three years) is related to finance and insurance. The theme of the research project will lie within areas such as: simulation and risk modelling using advanced statistical and machine