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

Position Highlights

The University of Arizona College of Information Science focuses on the intersection of people, data, and technology, offering innovative programs in information science, data science, cybersecurity, game design, and immersive technologies. Established in 2023 and expanded in 2025, the college provides STEM-designated undergraduate and master's degrees, and a PhD. in Information. With nationally ranked programs such as the #1 Best Online Bachelor's in Cybersecurity, #4 Best Master's in Data Science, and #10 Global Ranking of Library an Information Science Programs, we emphasize computational thinking, ethical reasoning, and multicultural communication while driving research and partnerships such as Arizona Cybersecurity Academy, AI Core, Gaming and Virtual Worlds, Human -Centered Computing, and many other areas of research.

The University of Arizona's College of Information Science invites you to apply to the role of Research Scientist IV. In this exciting role, you will serve as a senior researcher with Dr. Peter Jansen on a DARPA funded research project in artificial intelligence and natural language processing focused on scientific feasibility assessment. The project investigates methods for evaluating the feasibility of scientific claims using AI approaches that focus on autonomously building, running, and evaluating code-based experiments, that may integrate simulators, tools, literature-based knowledge, and other methods.

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. In this position, you will work closely with internal teams, student researchers, and external collaborators to contribute to research strategies and the development of new methodological directions.

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.

Applicants must be currently authorized to work in the United States.

Outstanding U of A benefits include health, dental, and vision insurance plans; life insurance and disability programs; paid vacation, sick leave, and holidays; U of A/ASU/NAU tuition reduction for the employee and qualified family members; retirement plans; access to U of A recreation and cultural activities; and more!

Full-time, benefits-eligible employees also enjoy a comprehensive paid time off program. For more information on the university's total benefits and compensation package, please visit: https://talent.arizona.edu/compensation-and-benefits

The University of Arizona has been recognized for our innovative work-life programs. For more information about working at the University of Arizona and relocations services, please click here.

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.
• 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.
• 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.

This job posting reflects the general nature and level of work expected of the selected candidate(s). It is not intended to be an exhaustive list of all duties and responsibilities. The institution reserves the right to amend or update this description as organizational priorities and institutional needs evolve.

Minimum Qualifications

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

Preferred Qualifications

• Ph.D. in Computer Science or a closely related field.
• Record of publications in top-tier AI/NLP venues.
• Demonstrated experience developing substantial research software systems.
• Experience in AI for science, literature-based discovery, or scientific knowledge extraction.
• Experience building or studying autonomous or semi-autonomous coding agents.
• Experience designing or implementing automated experimentation or simulation-based evaluation systems.
• Experience or demonstrated interest in automatic evaluation of difficult-to-evaluate open problems, without gold labels, using rubric, proxy metric, or other methods.
• Experience working with medium-to-large research codebases (tens of thousands of lines).
• Experience with high-performance computing environments.
• Experience releasing open-source projects.
• Experience building AI agents, tool-using models, or code generation systems.

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

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

Expected End Date: 7/30/2027

Contact Information for Candidates

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

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 the Additional Document:

• Representative code samples from your prior work.

The application window is anticipated to close on Monday, March 30, 2026.