Senior Research Scientist, Information Science (Extended Temporary) (Remote Work Available)

Posting Number req26830

Department Information Science

Department Website Link https://infosci.arizona.edu/

Location To Be Determined

Address USA

Position Highlights

The University of Arizona's College of Information Science invites you to apply to the role of Senior Research Scientist (Research Scientist IV). As a Senior Research Scientist, you will provide high-level scientific and technical leadership, oversee the design and implementation of experimental pipelines, maintain robust research codebases, and ensure methodological rigor across large-scale empirical studies. This position works closely with internal teams, student researchers, and external collaborators to advance research strategies and develop new methodological directions. This is a grant-funded project with a time-sensitive timeline. The position is anticipated to start by no later than the end of September 2026. The final candidate determination will take into consideration the candidate’s availability to start in alignment with the project timeline. Candidates working anywhere in the U.S. may be considered for a remote assignment. If you are selected for this position and are employed to work remotely from outside of Arizona, your overtime exemption status will depend on the laws of the state where you perform your work. For employees working outside of Arizona, you may be hired as an hourly employee in accordance with state laws. A comparable hourly rate range would be: $36.32 - $47.22. These changes would not affect the position duties as outlined. This is an Extended Temporary Employment (ETE) position.

Duties & Responsibilities

In this role, you will:

• Lead the design, implementation, and evaluation of AI/NLP systems for scientific feasibility assessment; develop and test integrated pipelines combining literature-based discovery, structured knowledge extraction, simulation, and code-based experimentation; run experiments and benchmarking at scale.
• Architect and maintain high-quality research codebases in Python and related tools; implement automated experimentation frameworks, simulation integrations, and evaluation infrastructure; ensure reproducible artifacts, logging, and documentation for large-scale empirical studies.
• Design and execute systematic empirical analyses of model behavior and experimental outcomes; analyze large-scale datasets, intermediate outputs, and logs to diagnose system performance, refine methods, and ensure research rigor.
• Design and execute user studies of human scientific feasibility assessment.
• Lead and co-author conference and journal papers for top-tier AI/NLP and machine learning venues; prepare manuscripts for peer-reviewed publication; create clear technical presentations and present findings at national and international conferences.
• Develop research directions, experimental methodology, and project roadmaps; assist with preparation of technical reports, and research documentation as needed.
• Drive collaboration, manage relationships, and provide technical guidance to student researchers where appropriate.
• Contribute to a collegial, respectful, and collaborative research environment through professional and constructive communication.
• Coordinate with collaborators within and outside the University as needed for joint experiments, data integration, and research dissemination.

Knowledge, Skills, and Abilities:

• Exceptional programming ability, particularly in Python, and strong software engineering practices.
• Demonstrated ability to design and maintain substantial research codebases.
• Strong knowledge of AI/NLP research methods, including experimental design, evaluation, and benchmarking.
• Knowledge of user studies, IRB protocols, human subjects research.
• Strong demonstrated ability at hands-on empirical research, including extensive interaction with generating and analyzing large volumes of data, intermediate representations, and experimental outputs.
• Familiarity with Linux-based research environments, Git, containerization (e.g. Docker), and reproducible workflows.
• Ability to work independently in a research-driven, small-lab setting.
• Strong written and verbal communication skills.

Minimum Qualifications

PhD in a related discipline required. Minimum of 8 years of relevant work experience, or equivalent combination of education and work experience.

Preferred Qualifications

PhD in Computer Science or a closely related field. Record of publications in top-tier AI/NLP or HCI venues. Demonstrated experience developing substantial research software systems. Experience in AI for science, literature-based discovery, or scientific knowledge extraction. Experience building or modifying AI agents, tool-using models, or code generation systems. Experience with high-performance computing environments. Experience releasing open-source projects. Experience executing large user-studies with human participants. Experience studying code generation systems (e.g. Claude Code, Open AI Codex, etc.)

FLSA

Exempt

Full Time/Part Time

Full Time

Number of Hours Worked per Week

40

Job FTE

1.0

Work Calendar

Fiscal

Job Category

Research

Benefits Eligible

Yes - Full Benefits

Rate of Pay

$75,540 - $98,201

Compensation Type

salary at 1.0 full-time equivalency (FTE)

Grade

10

Compensation Guidance

The Rate of Pay Field represents the University of Arizona’s good faith and reasonable estimate of the range of possible compensation at the time of posting. The University considers several factors when extending an offer, including but not limited to, the role and associated responsibilities, a candidate’s work experience, education/training, key skills, and internal equity. The Grade Range represents a full range of career compensation growth over time. The university offers compensation growth opportunities within its career architecture. To learn more about compensation, please review our Applicant Compensation Guide and our Total Rewards Calculator.

Career Stream and Level

PC4

Job Family

Researchers & Scientists

Job Function

Research

Type of criminal background check required:

Name-based criminal background check (non-security sensitive)

Number of Vacancies

1

Target Hire Date

9/14/2026

Expected End Date

7/30/2027

Contact Information for Candidates

Peter Jansen, Ph.D. Associate Professor, College of Information Science pajansen@arizona.edu

Open Date

8/19/2026

Open Until Filled

Yes

Documents Needed to Apply

Curriculum Vitae (CV), Cover Letter, and One Additional Document

Special Instructions to Applicant

In addition to your CV and cover letter, please submit the following as your additional document: At least one substantial research codebase, authored by the applicant (not an AI model, or a collaborator). Links to open published software (e.g. Github) preferred. The application window is anticipated to close on Thursday, August 27, 2026.

Notice of Availability of the Annual Security and Fire Safety Report

In compliance with the Jeanne Clery Campus Safety Act (Clery Act), each year the University of Arizona releases an Annual Security Report (ASR) for each of the University’s campuses. These reports disclose information including Clery crime statistics for the previous three calendar years and policies, procedures, and programs the University uses to keep students and employees safe, including how to report crimes or other emergencies and resources for crime victims. As a campus with residential housing facilities, the Main Campus ASR also includes a combined Annual Fire Safety report with information on fire statistics and fire safety systems, policies, and procedures. Paper copies of the Reports can be obtained by contacting the University Compliance Office at cleryact@arizona.edu.