Interested in this Research Scientist role at University of Arizona?
Apply Now →Skills & Technologies
About This Role
Posting Number req27227
Department Arizona Geological Survey
Department Website Link https://azgs.arizona.edu/
Location Tucson Campus
Address Tucson, AZ USA
Position Highlights The Arizona Geological Survey at the University of Arizona invites you to apply to the role of Geophysicist (Researcher/Scientist III).
This role is ideal for a field-oriented researcher with expertise in collecting and analyzing magnetotelluric (MT) and/or electrical resistivity (ER) data and performing inversion models that can be integrated with other geophysical datasets such as gravity, aeromagnetic, and seismic data for subsurface energy resource characterization. The Geophysicist will design, implement, and actively participate in field-based geophysical data collection campaigns; process raw datasets; and integrate multiple large datasets to develop 2D and 3D subsurface models.
The Arizona Geological Survey (AZGS) provides trusted geologic information that enhances public understanding of Arizona's geology, natural hazards, landscapes, and mineral resources. Working closely with state, tribal, local, and industry partners, AZGS delivers technical expertise and guidance to support informed decision-making and responsible land and resource management. Through its mission, AZGS helps advance public safety, sustainable development, and the effective stewardship of Arizona's geologic resources. The AZGS provides a working experience with opportunities to learn new techniques, collaborate with other scientists, and fosters an environment of scientific growth. Specifically, researchers at the AZGS are encouraged to develop their own projects with opportunities to learn new skills.
Visa sponsorship is not available for this position.
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!
The University of Arizona has been recognized for our innovative work-life programs.
Duties & Responsibilities
- Design, permit, and manage field-based geophysical data collection campaigns in challenging Arizona terrain, with emphasis on MT data collection.
- Perform quality control and troubleshoot geophysical equipment.
- Conduct fieldwork individually and as part of a team to accomplish scientific tasks in support of the Geophysics and Energy Geology Groups.
- Process geophysical datasets, with specific emphasis in MT, and generate 2D/3D inversion models.
- Create and manage large geologic and geophysical datasets in multiple, often simultaneous, projects related to energy resources and subsurface geology in Arizona.
- Aid in field deployments for passive seismic systems and help maintain the AZGS broadband seismic network.
- Participate in writing proposals for external funding from federal and state agencies and private partners.
- May lead or co-lead development of proposals.
- Will co-author inversion models, cross sections, technical reports, peer-reviewed scientific papers and will give public and scientific presentations.
Knowledge, Skills, and Abilities
- Expert knowledge of geophysical data collection methods, with an emphasis on magnetotellurics.
- Expertise in field deployment and management of field operations.
- Good technical writing skills.
- Good communication skills; able to effectively present results to people unfamiliar with MT.
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
- Master's degree in Geology or a related field, AND a minimum of three (3) years of relevant work experience is required.
- Ability to drive according to the University Fleet Safety Policy.
Preferred Qualifications
- Experience in field deployments of MT or electrical resistivity technologies.
- Experience with data analysis in Python.
- Experience processing S-EGY, mSEED, or other time-series geophysical datasets.
- Experience post-processing magnetotelluric datasets.
- Experience interpreting MT datasets.
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 DOE
Compensation Type salary at 1.0 full-time equivalency (FTE)
Grade 8
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 PC3
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
Expected End Date
Contact Information for Candidates Randi Bellassai
Assistant Director
Open Date 10/2/2026
Open Until Filled Yes
Documents Needed to Apply Resume and Cover Letter
Special Instructions to Applicant
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 [email protected].
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 9,653 AI roles we're tracking, Research Scientist positions make up 2% of the market. At University of Arizona, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
University of Arizona AI Hiring
University of Arizona has 1 open AI role right now. They're hiring across Research Scientist. Based in Tucson, AZ, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (193) are outnumbered by mid-level (4,500) and senior (3,455) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.