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Field
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communication systems and edge/cloud architectures; Experience in processing large datasets and scientific computing; Knowledge of Distributed Acoustic Sensing (DAS) systems, fiber-optic sensing, or distributed
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scalable bioinformatics pipelines on cloud-based infrastructure. The Research Fellow will be responsible for the code base supporting the large-scale genomic processing and analysis pipelines at the SMaHT
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discipline. Additional Qualifications Experience with running relevant numerical models (GCMs, mesoscale cloud-permitting or large eddy simulations) is desirable. Special Instructions Interested candidates
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AI models to automate QA/QC processes, enabling real-time verification, anomaly detection and consistency checks across records. Develop a cloud-based verification platform for digital data collection
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testing, version control, clear documentation, and continuous improvement of development infrastructure (e.g., CI/CD, Docker, cloud-based services). Carry out Risk Assessment, and ensure compliance with
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. Familiarity with Salesforce, Marketing Cloud, iwave and CMS platforms. Proficiency in Microsoft Office Suite (Word, Excel, PowerPoint) and Google Workspace. Knowledge or interest in science, international
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or single-cell genomics analysis. Familiarity with graph neural networks, transformers, generative AI or foundation models. Experience working with cloud/HPC environments, workflow orchestration
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), spatial statistics, or cloud computing Experience working in collaborative research teams Valid driver’s license and be able to successfully pass a driver’s record check Physical Requirements & Working
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in Python and/or R Experience with cloud computing and high-performance computing environments Ideal Candidate Profile We are seeking a computational biologist, biostatistician or bioinformatician with
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networks and/or edge-cloud continuum Document knowledge about the system performance evaluation of computer systems and networks for interactive applications, preferably with AR/VR/XR, robotics, haptics