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Mathematical Modeling Postdoc Jobs in Arizona (NOW HIRING)

Mathematical Modeling Postdoc information

What is the difference between Mathematical Modeling Postdoc vs Data Scientist?

AspectMathematical Modeling PostdocData Scientist
Required CredentialsPhD in Mathematics, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; PhD preferred
Work EnvironmentAcademic research institutions, universities, research labsCorporate, tech companies, startups, or consulting firms
Industry UsageResearch projects, academic publications, grant-funded studiesBusiness analytics, product development, data-driven decision making
Common Search & ComparisonYesYes

While both roles involve analytical skills and data handling, Mathematical Modeling Postdocs focus on academic research and developing theoretical models, whereas Data Scientists apply data analysis techniques to solve practical business problems. The choice depends on whether you prefer research-oriented work or industry applications.

What does a Mathematical Modeling Postdoc do?

A Mathematical Modeling Postdoc conducts advanced research using mathematical techniques to analyze and solve complex real-world problems in fields such as biology, engineering, physics, or social sciences. They typically develop and apply mathematical models, run simulations, analyze data, and interpret results to support scientific or industrial projects. Postdocs in this role often collaborate with interdisciplinary teams, publish research findings, and may also assist in mentoring students or contributing to grant proposals.

What are some common challenges faced by Mathematical Modeling Postdocs when transitioning from academic research to collaborative industry projects?

Mathematical Modeling Postdocs often encounter challenges when moving from academic research to industry settings, particularly in adapting to faster-paced timelines and working within interdisciplinary teams. In industry, projects may require quick prototyping and the ability to communicate complex mathematical concepts to non-experts, such as engineers or business stakeholders. Building effective collaborations and aligning research goals with organizational objectives can also be a significant adjustment. However, these challenges provide valuable experience and broaden career prospects in both academia and industry.

What are the key skills and qualifications needed to thrive as a Mathematical Modeling Postdoc, and why are they important?

A Mathematical Modeling Postdoc requires an advanced degree (typically a PhD) in mathematics, applied mathematics, or a related quantitative field, along with strong analytical and problem-solving abilities. Expertise with programming languages such as Python, MATLAB, or R, and experience with simulation software or computational tools, are commonly expected. Strong communication, collaboration, and critical thinking skills help in presenting findings and working effectively within research teams. These competencies are vital for developing robust models, interpreting complex data, and contributing to innovative research outcomes.
What cities in Arizona are hiring for Mathematical Modeling Postdoc jobs? Cities in Arizona with the most Mathematical Modeling Postdoc job openings:
Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)

Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)

University of Arizona

Tucson, AZ • On-site

Full-time

Medical, Dental, Vision, Life, PTO

Posted 29 days ago


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7.0

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Job description

Postdoctoral Researcher - Computational biology/Cancer bioinformatics (Full Time)
Posting Number
req26025
Department
Cancer Center Division
Department Website Link
https://cancercenter.arizona.edu/
Location
Tucson Campus
Address
1501 N. Campbell Ave, Tucson, AZ 85719 USA
Position Highlights
The Theodorescu Lab within the University of Arizona Cancer Center (UACC) and Padi Labs within the Department of Molecular and Cellular Biology are looking to hire a joint postdoctoral researcher with a strong background in computational biology and/or cancer bioinformatics. This project will be focused on integrating rich, multimodal 'omics data from cell lines and animal models, with the goal of identifying mechanisms leading to transformation and cancer. To identify such cancer-driving effects, we combine genomics, proteomics, and spatial transcriptomics data generated in the Theodorescu Lab with techniques for network inference, epigenetic rewiring, and dynamic modeling developed in the Padi Lab. Examples of the type of work that will be undertaken can be seen by our papers by Chen (Nature. 2025 Jun;642(8069):1041-1050), Abdel-Hafiz (Nature. 2023 Jul;619(7970):624-631), Gouin (Nature Commun. 2021; 12;12(1)), Ben Guebila (Genome Biology. 2023; 24(1):45) and Yang (Journal of Clinical Investigation. 2025; 135(7)). Our final goal is to identify novel biomarkers and interventions for cancer that will improve patient outcomes.
This individual would join two vibrant groups that closely collaborate to bridge the gap between innovative cancer research and state-of-the-art computational modeling. The successful candidate will be a driven, creative, team-oriented individual with an aptitude for quantitative/informatic methods and a passion for helping to discover fundamental cancer biology mechanisms that have potential clinical impact and thus can be moved eventually towards a clinical setting. We employ a wide variety of computational and experimental approaches and seek individuals with a strong understanding of both bioinformatics and molecular biology. Experience gained in our laboratory will help the candidate to become competitive for permanent positions in either academia or industry. We welcome applications from both recent PhD or MD/PhD recipients and individuals seeking additional postdoctoral training. For more information, please visit: https://cancercenter.arizona.edu/person/dan-theodorescu-md-phd and https://www.padilab.com.
Outstanding U of A benefits include health, dental, vision, and life insurance; paid vacation, sick leave, and holidays; UA/ASU/NAU tuition reduction for the employee and qualified family members; access to UA 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 relocation services, please click here.
Duties & Responsibilities
  • Design and perform quantitative data analysis. Keep detailed record of codebase with documentation and share the results with the Principal Investigators.
  • Develop, adapt, and implement new research techniques and algorithms.
  • Analyze, interpret, present, and interpret the data clearly and accurately.
  • Perform routine and complex data analysis procedures throughout training period.
  • Assist in preparation of grant proposals with the PIs but is not responsible for generating grant funds.
  • Participate in publications and presentations as author or co-author.
  • Meet with both PIs on a regular basis to discuss research progress and plans.
  • May be asked to write small grant proposals or NRSA/T32 applications.
  • Spends about 75% of time on computational analysis and 25% of time on writing articles/analyzing data/online research.

Knowledge,Skills, and Abilities:
  • Ability to work semi-independently on research projects within an area of specialization.
  • Thorough technical and theoretical knowledge of research projects and the objectives to be accomplished during this post-doctoral appointment.
  • Demonstrated aptitude to perform quantitative analyses, generate reproducible code, and interpret results in a biological context.
  • Strong understanding of both bioinformatics andmolecular biology.

Minimum Qualifications
  • Doctorate(PhD or MD/PhD) in computational biology, physics, math, computer science, orrelated field.

Preferred Qualifications
  • Outstanding publication record from prior graduate and/or postgraduate training and/or existing extramural funding.

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
Dr Megha Padi,mpadi@arizona.edu
Open Date
5/15/2026
Open Until Filled
Yes
Documents Needed to Apply
Curriculum Vitae (CV) and Cover Letter
Special Instructions to Applicant
Application: The online application should be completed in its entirety. Blank or missed information may be considered an incomplete submission.
Cover Letter: Should clearly indicate how your skills and professional employment experience meet the Minimum and the Preferred qualifications (if applicable).
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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