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Job Title:

Department:

Postdoctoral Scholar in Artificial Intelligence (AI) in and High Performance Computing

The Systems and AI (SAI) Research Lab in the Department of Computer Science and Engineering at The Ohio State University conducts interdisciplinary research in scalable software systems, artificial intelligence and machine learning (AI/ML), edge-to-cloud computing platforms, digital agriculture, and advanced cyberinfrastructure. The lab develops and evaluates novel computational methods, software platforms, and data-driven workflows that enable scientific discovery, real-world deployment, and successful execution of sponsored research projects.

The SAI Research Lab seeks a highly motivated and accomplished Postdoctoral Scholar to conduct independent and collaborative research at the intersection of AI systems, distributed and high-performance computing, edge-to-cloud platforms, and domain-driven applications such as digital agriculture and environmental intelligence. The Postdoctoral Scholar will work closely with the faculty lead, students, research staff, and external collaborators to formulate research questions; develop novel methods, algorithms, software, and cyberinfrastructure; design and execute rigorous experimental evaluations; disseminate findings through peer-reviewed publications and presentations; and contribute to proposal development and sponsored-project deliverables.

This position provides an opportunity to lead high-impact research projects, mentor graduate and undergraduate researchers, strengthen the lab’s software and experimental infrastructure, and help translate research innovations into robust, reusable platforms and real-world deployments. The successful candidate will demonstrate scholarly independence, strong technical depth, excellent written and oral communication skills, and the ability to work effectively across interdisciplinary teams.

Qualifications

Required:

Experience: 0-1 Years.

Education: Doctorate in computer science or computer engineering.

• Doctoral degree in computer science, computer engineering, electrical engineering, data science, agricultural engineering, or a closely related field, completed by the start date.
• Demonstrated research experience in one or more relevant areas, such as AI/ML systems, distributed systems, cloud computing, edge computing, high-performance computing, cyberinfrastructure, data-intensive computing, computer vision, digital agriculture, or scientific computing.
• Record of scholarly productivity appropriate to career stage, including peer-reviewed publications, technical reports, open-source software, or equivalent research contributions.
• Strong programming and software-engineering experience in languages and environments relevant to the lab’s work, such as Python, C/C++, Java, JavaScript/TypeScript, containerization, cloud platforms, workflow systems, distributed computing frameworks, and version-control systems.
• Demonstrated ability to independently design experiments, analyze results, prepare technical documentation, and communicate research findings in writing and presentations.
• Ability to work effectively in a collaborative, interdisciplinary research environment.

Desired:

• Experience developing AI/ML-enabled applications for scientific, agricultural, environmental, geospatial, or cyber-physical systems.
• Experience with GPU computing, distributed training or inference, high-performance computing systems, cloud-native platforms, edge devices, Internet of Things (IoT) systems, or federated/distributed data pipelines.
• Experience deploying and evaluating software systems across heterogeneous computing environments, including edge, cloud, cluster, and on-premise infrastructure.
• Experience contributing to externally funded research projects, including proposal preparation, technical reporting, milestone tracking, and sponsor-facing demonstrations.
• Experience mentoring undergraduate or graduate researchers.
• Evidence of open-source software development, reproducible research practices, dataset curation, or public release of research artifacts.
• Strong interest in translating foundational systems and AI research into practical tools, platforms, and deployments with measurable scientific or societal impact.

Additional Information:

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