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Phd Optimization Research Jobs in Texas (NOW HIRING)

SEMRON

ML Research Scientist

Austin, TX · On-site

Required : • PhD or equivalent research experience in machine learning, applied mathematics, or a related field • Strong understanding of quantization, model optimization, and numerical methods ...

webAI

AI Research Scientist

Austin, TX · On-site

... of optimization techniques including quantization, distillation, pruning, and hardware-aware ... or PhD in Machine Learning, Computer Science, AI, or a related field • Experience with ...

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Phd Optimization Research information

What is a PhD in optimization research?

A PhD in Optimization Research is an advanced academic degree focused on developing and analyzing mathematical models and algorithms to find the best possible solutions to complex problems. This field often involves linear and nonlinear programming, combinatorial optimization, and stochastic processes, and is applied in areas such as operations research, machine learning, logistics, and engineering. Graduates are prepared for careers in academia, industry, or research institutions, where they work on improving decision-making processes and resource allocation. The program typically involves coursework, comprehensive exams, and original research leading to a dissertation.

What is the difference between Phd Optimization Research vs Data Scientist?

AspectPhd Optimization ResearchData Scientist
Required CredentialsPhD in Operations Research, Applied Mathematics, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; some roles prefer PhD
Work EnvironmentResearch labs, academia, R&D departments in industryTech companies, finance, healthcare, consulting firms
Industry UsageFocus on developing optimization algorithms, mathematical modelingFocus on data analysis, machine learning, predictive modeling
Common Search/ComparisonYesYes

While both roles involve advanced analytical skills, Phd Optimization Research primarily focuses on developing and refining optimization algorithms and mathematical models, often in research or academic settings. Data Scientists analyze large datasets to extract insights and build predictive models, often applying machine learning techniques. The roles overlap in data analysis and quantitative skills but differ in their core focus and typical work environments.

What are the key skills and qualifications needed to thrive as a PhD optimization researcher, and why are they important?

To excel as a PhD Optimization Researcher, you typically need a doctorate in applied mathematics, computer science, operations research, or a related field, along with expertise in mathematical modeling and algorithm development. Proficiency with programming languages such as Python, MATLAB, or C++, and familiarity with optimization libraries and tools like Gurobi or CPLEX are commonly required. Strong analytical thinking, creativity, and effective communication skills help in formulating novel solutions and collaborating with interdisciplinary teams. These competencies are crucial for advancing research, solving complex optimization problems, and effectively disseminating findings within both academic and industry settings.

What are the typical collaborative projects that a PhD optimization researcher might work on within a multidisciplinary team?

PhD Optimization Researchers often collaborate on projects that integrate expertise from fields such as data science, engineering, computer science, and business analytics. These projects may involve developing and implementing advanced optimization algorithms to solve complex, real-world problems like supply chain management, resource allocation, or energy systems modeling. Team members typically contribute domain knowledge, data, and problem requirements, while the optimization researcher focuses on model formulation, algorithm selection, and solution analysis. Effective communication and adaptability are essential, as researchers must translate technical findings into actionable insights for stakeholders.

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What job categories do people searching Phd Optimization Research jobs in Texas look for?

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Cities in Texas with the most Phd Optimization Research job openings:

Phd Optimization Research jobs near you
Infographic showing various Phd Optimization Research job openings in Texas as of June 2026, with employment types broken down into 87% Full Time, 11% Part Time, 1% Contract, and 1% Nights. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution.

Quantitative Research Intern, PhD (Summer 2027)

Optiver

Austin, TX • On-site

Other

Re-posted 14 days ago

Job description

As a Quantitative Research Intern, you'll work alongside researchers, engineers, and traders to tackle some of the most challenging quantitative problems in global financial markets. You'll analyze large-scale datasets, develop predictive models and algorithms, and apply statistical and machine learning techniques to uncover patterns in market behavior. AI-driven research at Optiver is where competitive advantage is built, transforming ideas, models, and insights into trading strategies that operate in live markets.
This opportunity is also available in our Chicago office.
What You'll Do:
Led by our dedicated Education team, you'll build a strong foundation in market structure and options theory. This internship follows an apprentice-style learning model where you'll work alongside an experienced researcher and contribute to a project that's aligned with current business needs. Throughout the internship, you'll gain exposure to the AI tools and technologies that support research and development across the business, with the opportunity to contribute to several key areas:

  • Develop predictive models and machine learning systems to better understand market behavior and identify trading opportunities
  • Analyze large-scale market and order-flow data to uncover signals, evaluate hypotheses, and improve trading performance
  • Build and test statistical and stochastic models for pricing, forecasting, and risk management
  • Apply modern research techniques, including deep learning and AI-enabled workflows, to accelerate discovery and improve research efficiency
What You'll Get:
You'll join a culture of collaboration, continuous improvement, and excellence, surrounded by curious thinkers and creative problem-solvers. Together, you'll tackle some of the toughest challenges in the financial markets by leveraging cutting-edge machine learning research to develop innovative, real-world solutions.
In addition, you'll receive:
  • The opportunity to work alongside best-in-class professionals from over 40 different countries
  • The opportunity to earn a return internship or full-time offer in Chicago, Austin, or New York City based on performance
  • A highly-competitive internship compensation package
  • Optiver-covered flights, living accommodations, and commuting stipends
  • Extensive office perks, including breakfast, lunch, snacks, regular social events, clubs, sporting leagues, and more
What To Expect:
As part of our assessment process, you may be invited to participate in a multi-day, on-site evaluative program. Through hands-on workshops, technical discussions, and direct exposure to our researchers and traders, you'll gain insight into how research is applied at Optiver and how PhD students transition successfully into industry. Attendance and successful completion of this program may be required to receive an internship offer.
Who You Are:
  • Currently enrolled in a PhD program in Statistics, Computer Science, Machine Learning, Mathematics, or a related STEM field with outstanding academic performance
  • Expected graduation between December 2027 - June 2029 and available to intern during Summer 2027
  • Open to full-time opportunities upon graduation in 2028 or 2029
  • Solid foundation in mathematics, probability, and statistics
  • Excellent research, analytical, and modeling skills
  • Experience applying machine learning methods to real-world research problems, such as time-series analysis, prediction, forecasting, pattern recognition, optimization, or decision-making
  • Proficiency in any programming language
  • Strong interest in working in a fast-paced, collaborative environment
  • Fluent in English with strong written and verbal communication skills

Who We Are:
Optiver is a leading technology- and research-driven trading firm. Our teams of scientists, engineers, mathematicians, and traders work side by side to develop, test, and scale ideas that shape how we understand and trade global markets. Powered by a global platform built for rapid experimentation and iteration, we combine the scientific rigor of a research institution with the pace of a technology company.
Our differences are our edge. Optiver does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, physical or mental disability, or other legally protected characteristics.
Optiver is supportive of US immigration sponsorship for this role.
*Optiver has a global application re-apply policy for our intern and graduate roles. If you have completed an online assessment or interviewed for a quantitative graduate or internship role at any Optiver location in the past 8 months, please note that you are not yet eligible to reapply. We welcome you to re-apply to after the 8-month cool off period.

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