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Summer Computer Vision Postdoc Jobs in Arizona (NOW HIRING)

Forvis Mazars

Intern Audit Summer 2027

Tempe, AZ · On-site

$14.50 - $19.50/hr

... have Forward Vision and: * Solid technical accounting knowledge * Effective time management ... Strong computer skills preferred, including Microsoft Office suite * Ability to work well with a ...

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Summer Computer Vision Postdoc information

What is a summer computer vision postdoc?

A Summer Computer Vision Postdoc is a temporary research position, typically lasting a few months over the summer, for individuals who have recently earned a PhD in a relevant field such as computer science or electrical engineering. The role focuses on conducting advanced research in computer vision, which involves enabling computers to interpret and process visual information from the world. Postdocs work alongside faculty and research teams, contributing to projects, publishing papers, and gaining additional experience before pursuing faculty positions or industry roles. These positions often emphasize innovation, collaboration, and the practical application of state-of-the-art computer vision techniques.

What are the typical challenges faced by a summer computer vision postdoc working in a research environment?

As a Summer Computer Vision Postdoc, you may encounter challenges such as adapting quickly to new research topics, handling large and complex datasets, and optimizing algorithms for practical performance. Collaboration with interdisciplinary teams is common, requiring clear communication of technical concepts to colleagues from diverse backgrounds. Additionally, you will likely balance multiple projects within a limited timeframe, making effective time management and prioritization essential for success.

What are the key skills and qualifications needed to thrive as a summer computer vision postdoc, and why are they important?

To thrive as a Summer Computer Vision Postdoc, you need a strong background in computer vision, machine learning, and programming, typically supported by a PhD in computer science or a related field. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), image processing libraries (like OpenCV), and version control systems (e.g., Git) is essential. Excellent problem-solving abilities, research communication skills, and the ability to collaborate with multidisciplinary teams will make you stand out in this role. These skills ensure you can effectively develop novel algorithms, communicate findings, and contribute to advancing the state of computer vision research.

What are the most commonly searched types of Computer Vision Postdoc jobs in Arizona?

The most popular types of Computer Vision Postdoc jobs in Arizona are:

What are popular job titles related to Summer Computer Vision Postdoc jobs in Arizona?

For Summer Computer Vision Postdoc jobs in Arizona, the most frequently searched job titles are:

What job categories do people searching Summer Computer Vision Postdoc jobs in Arizona look for?

The top searched job categories for Summer Computer Vision Postdoc jobs in Arizona are:

What cities in Arizona are hiring for Summer Computer Vision Postdoc jobs?

Cities in Arizona with the most Summer Computer Vision Postdoc job openings:

Summer Computer Vision Postdoc jobs near you

Postdoctoral Research Associate, Systems and Industrial Engineering

Tucson, AZ • On-site

University of Arizona
Colleges, Universities, and Professional Schools • 10K+ employees
Learn more about University of Arizonaexternal

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 27 days ago

University Of Arizona rating

7.4

Company rating: 7.4 out of 10

Based on 69 frontline employees who took The Breakroom Quiz

Job description

Postdoctoral Research Associate, Systems and Industrial Engineering
Posting Number
req25668
Department
Systems and Industrial Engr
Department Website Link
https://sie.engineering.arizona.edu/
Location
Tucson Campus
Address
1127 E. James E. Rogers Way, Tucson, AZ 85721 USA
Position Highlights
The Department of Systems and Industrial Engineering seeks a Postdoctoral Research Associate to support research at the intersection of systems engineering and digital engineering, with an emphasis on advancing methods, tools, and architectures that enable modern engineering practice. The individual will contribute original scholarship and applied research, developing prototypes and capabilities that strengthen model-based and data-driven approaches. The position values interdisciplinary thinking, particularly where software development, emerging AI-enabled techniques, and systems modeling intersect. Responsibilities include publishing and presenting research results while helping shape and mature a digital engineering sandbox environment.
Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; U of A/ASU/NAUtuition reduction for the employee and qualified family members; access to U of A recreation and cultural activities; and more!
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
  • Author and co-author peer-reviewed journal papers targeting venues such as Systems Engineering (Wiley/INCOSE), SIMULATION (SCS/SAGE), Applied Ontology (IOS Press), and relevant IEEE/ACM journals.
  • Prepare and present conference papers at CSER, INCOSE IS, CESUN, and similar venues.
  • Contribute to technical reports and sponsor deliverables as needed.
  • Support the design and implementation of a digital engineering sandbox environment for capability prototyping, training, and experimentation.
  • Integrate emerging SE tooling (e.g., AI-assisted workflows, ontology-backed reasoning, requirements co-pilots) into the sandbox.
  • Ensure the sandbox supports controlled experimentation and repeatable demonstrations of SE capabilities.
  • Design, implement, and evaluate next-generation SE capabilities such as AI-augmented requirements engineering, automated conflict detection, model-based review support, and change impact analysis.
  • Advance selected capabilities from early maturity toward cross-context application using the project's assessment framework.
  • Prototype and test novel capability concepts informed by the transformation roadmap and sponsor priorities.
  • Conduct systematic literature reviews on digital engineering transformation, AI-augmented systems engineering, readiness assessment frameworks, and formal methods for SE.
  • Monitor and synthesize emerging SE capabilities.
  • Maintain a living literature database supporting project deliverables and journal submissions.
  • Design and execute controlled experiments, case studies, interviews, or surveys to generate rigorous evidence on SE capability effectiveness.
  • Collect and analyze data from sponsors and stakeholders on adoption barriers, governance gaps, and capability value.
  • Engage with professional organizations (e.g., INCOSE) to solicit expert feedback on the transformation roadmap framework and assessment methodology.
  • Mentor and supervise undergraduate research assistants working on project tasks.
  • Define scoped research tasks appropriate for undergraduate contribution (literature coding, data collection, prototype testing, documentation).
  • Review student work products and support their professional development (conference presentations, writing skills, research methods).

Knowledge, Skills, and Abilities
  • Knowledge of systems engineering principles, including model-based systems engineering (MBSE).
  • Knowledge of digital engineering concepts, tools, and transformation initiatives.
  • Skilled in utilizing Python.

Minimum Qualifications
  • Ph.D. in Systems Engineering, Computer Science, Industrial Engineering, or a closely related field. The selected candidate must have a conferred Ph.D. upon hire.
  • Experience publishing peer-reviewed journals and conference papers (e.g., IEEE, ACM, or comparable venues).
  • Experience designing and implementing research prototypes or software tools.

Preferred Qualifications
  • Experience with model-based systems engineering tools (e.g., SysML, Cameo, MagicDraw, Capella).
  • Demonstrate familiarity with digital engineering ecosystems and sandbox/testbed environments.
  • Experience with AI/ML techniques applied to systems engineering problems (e.g., requirements analysis, reasoning, automation).
  • Experience in ontology engineering, knowledge graphs, or semantic technologies.
  • Experience integrating heterogeneous tools and workflows (e.g., APIs, co-simulation, digital threads).

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
NIH salary guidelines, Depends on Experience
Compensation Type
salary at 1.0 full-time equivalency (FTE)
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
Alejandro Salado
alejandrosalado@arizona.edu
Open Date
4/20/2026
Open Until Filled
Yes
Documents Needed to Apply
Curriculum Vitae (CV) 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.Thesereports 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.

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