Research Job Opportunities

Position Overview

University of Idaho is seeking two Data Scientists to participate in an innovative National Science Foundation-funded project: “Crossing the Innovation Valley of Death: Democratizing Data and Artificial Intelligence for Research Administration.” The project offers the opportunity to pioneer the development of open-source AI solutions that will reshape how universities manage operations, while leading the democratization of data access and analysis across the research administration landscape. The goal is to drive institutional change by bridging the gap between cutting-edge technology and administrative efficiency. The candidates will help architect and implement AI-powered solutions to streamline workflows, design data integration strategies across multiple university systems and departments and create scalable, open-source tools that can be adopted by research administration units nationwide. One position will have a focus on technical development and implementation, while the other will combine technical expertise with training and knowledge dissemination responsibilities.

This posting will hire two applicants to meet the needs of this project.

Job Duties

Facilitate data engineering and integration efforts by (Estimated effort: 55%):

• Proactively identify, evaluate, organize and access existing data sources relevant to the GRANTED project mission and goals.
• Develop and nurture strong relationships with project partners internal and external to U of I.
• Work with Office of Sponsored Programs, IIDS, ORED, OIT, Institutional Research and others to periodically assess technical requirements of integrating project software into institutional workflows.
• Liaise with U of I offices, faculty, staff and leadership to acquire, document and ingest data into secure and approved repositories for archival, analysis and dissemination.
• Develop workflows compliant with relevant information security standards such as FERPA, NIST 800 171 and CMMC. Minimize use of sensitive personal information (SPI) where possible and participate in training and certification on handling sensitive data.
• Ensure interoperability with existing internal data repositories (e.g. VERAS, Banner, etc.) and external data networks (Web of Science, ORCID, PubMed, DataCite, Google Scholar, SciENcv, etc.)
• Deploy enterprise and open-source large language models to improve interoperability and process efficiency for research administration workflows.
• Benchmark and evaluate large language models for tasks related to process efficiency, automation and strategic analysis of institutional and external data.
• Fine tune, train and/or otherwise apply enterprise and open-source large language models for research administration use cases.
• Contribute to the design, maintenance, documentation and monitoring of processes and workflows related to research administration. These include data acquisition, preprocessing and maintenance, data integrity, data documentation (metadata) and data processing to enable automation, reproducibility and scalability.
• Design, implement and maintain databases in collaboration with technical staff within OSP, IIDS, OIT, ORED and other constituencies.
• Manage data through acquisition (database queries, web scraping), organization, cleaning and normalization and documenting data and processing steps with metadata.
• Develop and maintain modular software systems and related technologies to support interactive data management, visualization and dissemination.
• Build, customize and adapt AI applications, software and databases as needed to meet evolving partner and user-community requirements.

Lead development of innovative research data management and artificial intelligence solutions by (Estimated effort: 25%):

• Design and implement creative technical and logistical solutions to complex data management problems that pertain to U of I sponsored funding activity and impact.
• Leverage artificial intelligence, including large language models and multimodal LLMs to improve data quality and efficiency of data intensive workflows.
• Collaborate with GRANTED team, U of I staff and faculty and leadership to identify needs, customize solutions and train users and consumers.
• Train U of I staff on best practices for research data acquisition and data sharing, including how to use available AI applications, data sharing platforms and data management tools (e.g., searchable data catalog, data visualization and online collaboration systems and tools) and the importance of data security, data privacy and compliance with state and federal regulations.
• Develop and implement training materials necessary for the success of planned GRANTED tools and modules.
• Regularly engage with OSP and IIDS leadership to continually assess needs for additional training and communication.
• Participate in meetings, summits, conferences and other related events pertaining to the project objectives and activities.

Participate in partnership activities and events to build and maintain a community of practice by (Estimated effort: 15%):

• Travel to and host GRANTED partners at U of I to develop a robust community of practice for the GRANTED program.
• Attend relevant Research Administration meetings and conferences, such as NCURA Region VII annual meeting, NCURA National meeting, IMURA, etc.) to engage with partners, generate interest and partnerships for GRANTED and learn more about research administration needs.
• Present materials, tools and training at Research Administration events.

Continue professional development (Estimated effort: 5%):

• Travel to and host GRANTED partners at the U of I to develop a robust community of practice for the GRANTED program.
• Attend relevant Research Administration meetings and conferences, such as NCURA Region VII annual meeting, NCURA National meeting, IMURA, etc.) to engage with partners, generate interest and partnerships for GRANTED and learn more about research administration needs.
• Present materials, tools and training at Research Administration events.

Requirements

Education

• Bachelor’s Degree

Experience

• Two years in a data scientist or data engineering type position
• Programming in one or more computer languages commonly used in data science (e.g., Python, R, Julia, MATLAB)
• Designing and using relational databases, including demonstrated experience with writing SQL queries
• Collecting, organizing and managing large data sets
• Using APIs and web scraping tools to develop and connect large interoperable databases
• Implementing best practices for rigorous data security
• Working both independently and within a team managing multiple projects with competing deadlines

Preferred Qualifications

• A Masters or PhD in data science, data engineering, data analytics, computer science, business analytics, management information systems (MIS), statistics, mathematics, software engineering, informatics or related field
• Experience in a Research Administration setting, preferably at an Institution of Higher Education
• Developing and presenting data visualizations in static and interactive formats to communicate analyses, methods and results
• Experience providing training and giving presentations to groups of people
• Experience with retrieval augmented generation using large language models
• Proven ability to effectively communicate with peers and coworkers on complex research and technology issues in both group and individual settings
• Understanding of and experience with institutional research data
• Experience with the following technologies:
  • Web Development with HTML, CSS, Javascript as well as PHP or Python
  • Understanding of common metadata standards and practices
  • Web service Application Programming Interfaces (APIs)
  • JSON, XML, XSLT and related tools
  • Linux operating systems
  • Software configuration and versioning tools such as: Git/GitHub, Subversion, etc
  • AI integration using Langchain or other pipelines
• Experience with the use, training and fine-tuning of artificial intelligence and large language models
• Knowledge and understanding of computer security and compliance frameworks such as CMMC and NIST
• Experience writing IT programming specifications
• Experience in handling confidential information
• Experience with using high performance computing environments
• Excellent written and verbal communication and interpersonal skills as demonstrated in application materials
• Self-motivated, team-oriented attitude as demonstrated in application materials

Additional information

• Apply through the University of Idaho Careers page.
• In your application, please address all the minimum requirements in the Letter of Qualification. Preferential review of applicants to begin Tuesday, Jan. 28, 2025.