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About Us PharosAI offers a unique cancer AI product development ecosystem for drug discovery and clinical applications, democratising access to data, AI models, technologies, and capabilities
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performance under diverse operating scenarios, including power limitations, ambient environmental conditions, and human-device interactions • Validate simulation models using experimental data or benchmark
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enhanced interference resilience against different interfering systems. Develop, with colleagues, a spectrum sharing database for use by the JOINER community and design and develop models using AI/ML and
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information about AbbVie, please visit us atwww.abbvie.com . Follow @abbvie onX ,Facebook ,Instagram ,YouTube ,LinkedIn andTik Tok . Job Description Program Overview AbbVie needs outstanding individuals willing
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quantitative techniques (e.g., NLP, classification, clustering), statistical modelling, and other computational techniques Process large scale text data sets in multiple languages Create documentation for data
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interest or experience in RNA therapeutics and high-throughput innovation. Enthusiasm for interdisciplinary collaboration, particularly with computational team members focused on AI model development
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-based role focusses on electromagnetic design, computational modelling (e.g., COMSOL, CST, ANSYS), dielectric characterisation, and testing that help to bridge the gap between laboratory-scale research
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features in alloys, to aid future alloy design. The UNSW team, lead by A/Prof Patrick Burr, will provide the modelling contributions, and the team at USyd, led by Prof Julie Carney and Dr Ranming Liu, is in
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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the colleagues to develop and implement an ambitious quantitative research programme To develop new models for understanding key determinants of community connectedness To engage in data science debates, notable