Postdoctoral Researcher

Job Summary We are seeking a highly talented postdoctoral researcher with experience and interest in state‑of‑the‑art AI technologies, data science, and research software engineering. This position offers the opportunity to work in a world‑renowned research institute alongside faculty, software engineers, PhD students, and PostDocs on the development of cutting‑edge AI‑ready/agentic infrastructure for data and model discovery, model metadata extraction, and scholarly intelligence. The project will explore conceptual frameworks and system architecture to support data trust in the context of AI‑enabled science workflows. Experience in developing and deploying software is desired. We are extending and maintaining the National Data Platform to support a new generation of discovery capabilities targeting AI‑enabled (agentic) science workflows. Building on ideas pioneered by the Democratizing Data project, this project will explore approaches to discover data and models that are trusted and fit for use by leveraging contextual information about their use derived from a range of sources, including published literature. The approach includes extracting, linking, and presenting evidence from records to help users understand where models are used, how they are applied, what tasks they support, and how they evolve across scientific domains. The successful candidate will contribute directly to the research and implementation of workflows for AI model identification, publication mining, metadata engineering, search and retrieval, and interactive user‑facing systems. The role includes support for integration, development, deployment, maintenance, UI/UX, containerization, automation, and system‑level optimization. Research Focus of This Position AI models mentioned or used in publications Model families, versions, checkpoints, and architectures Tasks and scientific domains in which models are applied Evidence of reuse, benchmarking, fine‑tuning, and comparison Links among papers, models, repositories, benchmarks, and supporting resources Search, ranking, and visualization interfaces for model‑centric scholarly exploration Opportunities for Professional Development Contribute to high‑impact interdisciplinary research Publish and present work in relevant venues Collaborate with experts in AI, data systems, and scientific computing Gain hands‑on experience with production‑grade research software and infrastructure Mentor students and junior developers Shape the future of AI‑ready scholarly discovery platforms Work Environment You will contribute to cutting‑edge computational methods for AI‑ready model discovery, research knowledge extraction, and scientific search systems. We Offer Flexible working hours Professional career development opportunities Collaboration with a multidisciplinary and research‑driven team Access to strong computing and research infrastructure A competitive benefits package through the University of Utah Responsibilities Work with faculty, staff, and students in designing and developing computational tools in support of research projects. Aid in the specification of software requirements in coordination with faculty or team leads. Develop user interfaces and APIs with web front‑end technologies like HTML5, SCSS, Vue, React, TypeScript, D3.js, Node.js, Chart.js. Back‑end server component development with technologies such as Flask, Django, CKAN, ArangoDB, PostgreSQL, MongoDB, Redis, and Elasticsearch. Create and maintain build, testing, and deployment systems with Git, GitHub, Slack, Docker, AWS, Circle‑CI, webpack, npm, and many others. Develop high‑quality and well‑documented code. Build CI/CD workflows to validate changes across multiple targets. Profile and optimize performance for data throughput and latency. Interface with collaboration partners and participate actively in a collaborative work environment to turn requirements into optimal solutions on a large scale. Contribute actively to team discussions on architectural design and solutions by continuously looking for improvements. Research and stay current with project‑related scientific literature. Identify and implement creative solutions to overcome problems. Mentor postdocs, students, and junior software developers for best software practices. Support the end‑user community by responding to user questions posted on the discussion list, fixing bugs, and incorporating feature requests. Help with the project website and discussion boards for user support, developer support, and announcements. Contribute to teaching activities by preparing and presenting educational seminars. Minimum Qualifications Applicants must demonstrate the potential ability to perform the essential functions of the job as outlined in the position description. Preferred Qualifications Solid background and working knowledge of computer science fundamentals including algorithms, data structures, and object‑oriented programming. Experience with HTML and web technologies. Good knowledge of server technology and databases. Experience working with large codebases. Containerization (Docker) and building software for web deployment. Strong understanding of Linux toolchains and debugging tools. Debugging and critical thinking skills including identifying bottlenecks, bugs and devising solutions to these problems. Experience with GitHub Actions, GitLab CI, or similar CI/CD systems. PhD in Computer Science, Scientific Computing, Data Science, Informatics, AI/ML, or a closely related area, or equivalent research experience. Experience contributing to scientific computing frameworks. Knowledge of RDMA, libfabric, or similar low‑level communication APIs. MCP and NLP integration. UI/UX design. Scientific visualization. CyberSecurity and AAI (OAuth2, Keycloak, etc). Cloud deployment and Kubernetes. Able to work in a collaborative software development environment as well as working independently with minimal supervision and direction. Able to learn new tools and technologies. Being self‑motivated and having good organizational, communication, and teamwork skills is essential. Willingness and ability to collaborate in a highly diverse, multi‑disciplinary environment. Excellent oral and written communication skills necessary to effectively work in a multidisciplinary team environment. Communication and presentation skills to engage technical and non‑technical audiences. Strong interpersonal abilities and teamwork skills. Highly motivated to support research projects. Ability to manage time across simultaneous tasks. Contact Jess Tate – View email address on click.appcast.io #J-18808-Ljbffr University of Utah