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inference Develop distributed model training and inference architectures leveraging GPU-based compute resources Implement server-less and containerized solutions using Docker, Kubernetes, and cloud-native
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the university’s objectives and priorities. Utilize leadership and communication skills, along with a command of networking, cloud computing, virtualization, VoIP, and datacenter operations to manage the resources
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, context management, and implementation strategies for enterprise applications. Cloud Computing: Experience deploying and scaling AI systems in cloud environments (AWS, Azure, or GCP), with knowledge
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, Edge and Fog Computing SDN/NFV IoT protocols IoT architectures Digital Twin Network Security Smart Applications Device/Edge and Cloud based Machine Learning Position Type Academic Position Type Academic
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-code templates for reproducible environment setup Design and build scalable cloud infrastructure using compute, storage, and database services (e.g., EC2, Cloud Storage, Cosmos DB) Ensure high
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and methodological perspective of an engineer. Students build advanced design and engineering skills, enhance their knowledge in cloud computing, and develop machine learning algorithms. With a passion
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software development from the analytical and methodological perspective of an engineer. Students build advanced design and engineering skills, enhance their knowledge in cloud computing, and develop machine
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Bachelor’s degree in Computer Science, Information Technology, Business, or related field; technical certifications in relevant areas (e.g., cloud platforms, business analysis, AI/ML, digital solutions
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. Qualifications A PhDin Information Security, Cybersecurity, Computer Science, or a closely related discipline is preferred. Candidates should have relevant industry experience in cybersecurity, ideally in roles
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, Blockchain, Cloud Computing, Software Engineering, as well as Data Architecture & Engineering. In this role, the Teaching Faculty will report directly to the MGEN Executive Program Director. The selected