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Field
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05.07.2026, Academic staff Our research combines mathematical modeling, numerical simulation, scientific computing, and data-driven methodologies to improve the predictive capabilities and
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genomics modalities Background in immunology or inflammatory disease Experience with machine learning methods applied to large data Background in immunology, infectious disease, or inflammatory disease
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research involving large-scale public datasets, multi-omics integration, biological data harmonization, systems-level analysis, or related areas that synergize with the scientific goals, data products, and
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) Location: Kensington – Sydney, Australia (full-time on campus attendance required) About UNSW: UNSW isn’t like other places you’ve worked. Yes, we’re a large organisation with a diverse and talented
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large GPU clusters on cryoSTEM datasets in the multi-terabyte range. This position plays a pivotal role in supporting ongoing, high-impact research programs within our lab. The successful candidate will
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to join an interdisciplinary project at the interface of single-cell genomics, data integration, and developmental biology. The project focuses on the integration and analysis of multi-modal single-cell
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North America. More information about the Division of Heat Transfer can be found here: https://www.ht.energy.lth.se/english/ COMPEL, "COMPetence for the ELectrification of the transport system", is a
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foundation models, directly advancing the frontier of computational biology and machine learning. You will also implement parallel systems capable of training such models across large GPU clusters on cryoSTEM
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computational approaches to problems in molecular and cellular biology. Research may involve large-scale public datasets, biological data harmonization, representation learning, predictive modeling, foundation
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demonstrable experience in the analysis of large-scale biological datasets, applying statistical modelling and computational approaches to high-dimensional data such as bulk and single-cell sequencing, gene