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Talayeh Razzaghi

3 months ago

PhD Opportunity in Industrial Engineering, Optimization, Machine Learning, and Healthcare Analytics at the University of Oklahoma University of Oklahoma in United States

Degree Level

PhD

Field of study

Computer Science

Funding

The Ph.D. position is funded and begins in Fall 2026 or Spring 2027.

Deadline

Expired

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Country

United States

University

University of Oklahoma

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Keywords

Computer Science
Data Science
Machine Learning
Biomedical Engineering
Mathematics
Decision Making
Operations Research
Industrial Engineering
Salud Pública
Optimisation
Statistics

About this position

Ph.D. opportunity in Industrial Engineering at the University of Oklahoma with a funded research project starting in Fall 2026 or Spring 2027.

The project sits at the intersection of optimization, machine learning, and healthcare analytics, with the goal of developing data-driven methods that support decision-making and improve patient outcomes. This is a strong fit for applicants interested in operations research, data science, and applied research in healthcare settings.

Eligibility highlights: a recent or soon-to-be-completed M.S. degree (preferably within the last 0–2 years) in Operations Research, Industrial Engineering, Mathematics, or a closely related field; strong background in nonlinear and discrete optimization; proficiency in Python, R, or similar programming environments; machine learning experience preferred but not required; strong communication and teamwork skills.

Funding: the position is described as funded. No stipend amount, tuition details, or application deadline were provided.

How to apply: interested applicants should email their CV and a brief statement of interest to [email protected].

Funding details

The Ph.D. position is funded and begins in Fall 2026 or Spring 2027.

What's required

Applicants should have a recent or soon-to-be-completed M.S. degree, preferably within the last 0–2 years, in Operations Research, Industrial Engineering, Mathematics, or a closely related field. Strong background in optimization methods, including nonlinear and discrete optimization, is required. Proficiency in Python, R, or other relevant programming environments is required. Experience with machine learning is preferred but not required. Applicants should have a strong interest in interdisciplinary research connecting data science, optimization, and healthcare applications, along with strong communication skills and a collaborative mindset.

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University Name
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United States

Research Interests

Statistics

Business Analytics

Machine Learning

Industrial Engineering

Operations Research