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Field
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assessment criteria, which will be benefit are: Knwoledge and experience of cloud, monitoring & automation foundation Experience in foundation models and Large Language Models (LLMs). Experience in teaching
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, the regional campus in St. Cloud offers a wide range of patient experiences throughout students’ education in Greater Minnesota and prepares them to become exceptional clinicians and leaders for rural and
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cancer genomics resources and databases, including The Cancer Genome Atlas, cBioPortal, Genomic Data Commons, dbGaP, GEO, and related resources. Experience with high-performance computing, cloud-based
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causal inference, real-world evidence, multimodal data integration, or cloud/high-performance computing is a plus. The Postdoctoral Researcher will collaborate closely with biomedical informaticians
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understanding of data quality, reproducibility and robust analytical practice. Experience of SQL, cloud-based or high-performance computing environments, and Bayesian methods would also be valuable. Beyond
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machine learning frameworks (e.g., TensorFlow, PyTorch). Practical experience with cloud computing platforms (e.g., AWS, GCP, Azure). Additional Qualifications: Experience with multi-GPU model training and
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computing, cloud-based computing environments, workflow-management systems, containers, and/or software development practices. Experience with machine learning, predictive modeling, or artificial intelligence
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the McGill BioPortal. Develop and maintain reproducible analysis pipelines in R, Python, and shell on HPC / Slurm clusters and cloud environments (e.g., DNAnexus, Terra, AWS/GCP). Write first-author
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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maintain cloud-native genomic surveillance tools, datasets,and training resources. You will apply these to study insecticide resistance and the population structure of malaria mosquito vectors, generating