Post Doc Res Assoc w/Ret
University of Utah
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Benefits offered by this job
Job summary
University of Utah’s SCI Institute seeks a postdoctoral researcher with a strong background in AI, data science, and software engineering to help build AI-ready scholarly discovery platforms. You will collaborate with faculty, software engineers, PhD students, and postdocs to advance metadata extraction, model discovery, and evidence presentation for AI-enabled science workflows.
The role involves system design, UI/UX, containerization, deployment, and cross-team collaboration to create scalable
Qualifications
- Applicants must demonstrate the potential ability to perform the essential functions of the job as outlined in the position description.
Responsibilities
- Design and develop computational tools for AI-ready model discovery and scientific search systems.
- Develop user interfaces and APIs with HTML5, SCSS, Vue, React, Typescript, D3.js, node.js; ensure robust backend with Flask, Django, and databases.
- Build build, test, and deployment systems using Git, Github, Docker, AWS, Circle-CI, webpack, npm; maintain high-quality code.
- Mentor students and junior software developers; contribute to architectural design discussions and project documentation.
Skills
Education
Tools
Job description
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, a. 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 sience workflows. Experience and 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 discovery 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.
The SCI Institute is a world-class research institute located within the new Warnock Engineering Building on the University of Utah campus. We are a highly dynamic, driven group of over 170 faculty, staff, and students. The overarching goals of the SCI Institute’s scientific computing research are to create new techniques, tools, and systems, by which scientists may solve problems affecting various aspects of human life. We believe that to advance the state-of-the-art and create meaningful computational solutions for such complex systems, one needs to advance research in a number of areas within scientific computing, including: visualization, simulation, and modeling. The SCI Institute presents a highly challenging, collaborative work environment that can be deeply rewarding for the right individual. Further information is available at http://www.sci.utah.edu/
This position centers on the design and development of systems that enable discovery and analysis of AI models used in scientific research publications. Rather than cataloging datasets cited by papers, this effort focuses on identifying and organizing information about:
- 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
This work sits at the intersection of AI/ NLP, scholarly knowledge extraction, software engineering, data infrastructure, and human-centered discovery systems.
Through the Cyberinfrastructure Professionals (CIP) Cooperative (Co-Op) at the SCI Institute, the successful candidate will access a strong community of research computing and data experts working together to support and sustain SCI’s world-class research efforts. SCI’s CIPs perform a wide range of advanced services that positively impact research outcomes, improve researcher productivity, and strengthen the growing SCI research enterprise. The Co-Op provides faculty and research staff with a stable environment for mentoring, growth, training, communication, and planning across diverse research projects. This role offers exceptional opportunities to:
- 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
You will contribute to cutting-edge computational methods for AI-ready model discovery, research knowledge extraction, and scientific search systems.
- 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
- 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, 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
Applicants must demonstrate the potential ability to perform the essential functions of the job as outlined in the position description.
- 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.
- 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, and 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.
Note: This job description is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications required of employees assigned to the job.
The University of Utah values candidates who have experience working in settings with students and possess a strong commitment to improving access to higher education.
Veterans’ preference is extended to qualified applicants, upon request and consistent with University policy and Utah state law. Upon request, reasonable accommodations in the application process will be provided to individuals with disabilities.
Consistent with state and federal law, the University of Utah does not discriminate based upon race, ethnicity, color, religion, national origin, age, disability, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, pregnancy-related conditions, genetic information, or protected veteran’s status. The University does not discriminate on the basis of sex in the education program or activity that it operates, as required by Title IX and 34 CFR part 106. The requirement not to discriminate in education programs or activities extends to admission and employment. Inquiries about the application of Title IX and its regulations may be referred to the Title IX Coordinator, to the Department of Education, Office for Civil Rights, or both.
To request a reasonable accommodation for a disability or if you or someone you know has experienced discrimination or sexual misconduct including sexual harassment, you may contact the Director/Title IX Coordinator in the Office of Equal Opportunity and Title IX (OEO). More information, including the Director/Title IX Coordinator’s office address, electronic mail address, and telephone number can be located at the: University of Utah Non‑Discrimination page .
Online reports may be submitted at https://oeo.utah.edu
As per University of Utah policy 5-108: Transfer of Benefits Eligible Staff Members, a new hire to the University of Utah who is still serving a 12 month probationary period will not be hired into another University of Utah job (a transfer) until the successful completion of the probationary period.
University Human Resource Management
250 East 200 South, Suite 125 Salt Lake City, UT 84111
Contact us: (801) 581-2169 By Email: employment@utah.edu
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