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, and cloud-based resources for large-scale data analysis and model development. Using these rich data resources, we develop and apply advanced AI/ML methods to model tumor evolution, identify clinically
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); experience with cloud computing platforms (e.g., AWS, GCP, Terra) is a plus · Experience developing and training deep learning models, ideally with fluency in PyTorch or an equivalent framework, is a
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such as SQL and PostgreSQL, and may leverage cloud-based data platforms such as Databricks. Project 2: AI Adoption and Integration You will collaborate with PHI mentors to research and investigate
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, that can be realised using cloud compute infrastructure and other novel deployment architectures. Given our team's existing research skillset in novel machine learning approaches, we are recruiting a
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, that can be realised using cloud compute infrastructure and other novel deployment architectures. Given our team's existing research skillset in novel machine learning approaches, we are recruiting a
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authoring. Scientific project management experience, including coordination of multi-partner research activities. Experience with cloud computing platforms (e.g., AWS and Microsoft Azure). Experience with
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/software-engineering/), which has a strong track record in model-based software development and undertakes research on applications in areas such as healthcare, cloud technology and internet-of-things
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, data pipelines, database management, SQL, REDCap, cloud or high-performance computing environments, and reproducible research practices. Excellent communication, stakeholder engagement and collaboration
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FAIR cloud platforms for real-time genomic data exchange Create interactive dashboards showing genomic trends, variant emergence and geographical spread Translate genomic findings into public-health
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learning, generative AI or LLM-based systems, cloud computing, and the design and validation of algorithms for high-volume quantitative or sensor-derived data. Experience with wearable data, health