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Field
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Minimum 1 year of relevant experience Hands-on experience with R and/or Python and performing independent computational modeling. Ability to maintain data storage and usage of high-performance computing
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Australian National University | Canberra, Australian Capital Territory | Australia | about 21 hours ago
-cell RNA-sequencing data, with a focus on mouse models of age-related macular degeneration. The successful candidate will join Associate Professor Jean Wen’s research group, conducting independent
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of innovative computational procedures and methodologies, addressing a national skills shortage and enabling timely progress on a high-impact research initiative in modern econometric modelling. The role provides
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on JavaScript in your browser and try again. UiO/Anders Lien 4th August 2025 Languages English English English Postdoctoral Research Fellow in Ontology-Based Information Modelling and AI Apply for this job See
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Biomedical Engineering, Nanotechnology, or a related discipline. Strong hands-on experience in microfluidics (design, modelling, and experimental implementation) Knowledge of nanomaterials and their use in
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and modeling of properties and spectra of PFAS chemicals with the goals of improving detection of PFAS compounds, replacing PFAS in plasma etching processes, or identifying solid adsorbent additives
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experience 17% Superannuation and Flexible Working Arrangements Based at the RMIT Melbourne CBD campus About the Role We are seeking a Postdoctoral Research Fellow to join RMIT's Materials Modelling and
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) Based at our St Lucia Campus About This Opportunity We are seeking a Postdoctoral Research Fellow to join an ARC Linkage Project focused on advancing geomechanical modelling for underground CO₂ and H
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resistance, utilizing human and murine cells, orthotopic models, and Genetically Engineered Mouse Models (GEMMs). We are seeking a motivated and hard-working scientist with strong project leadership and
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. The project, "Building the bridge from GWAS to Breeder through multi-omic network data fusion", focuses on transforming GWAS discoveries into actionable breeding insights. Using sorghum as a model, the work