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Math Optimization Energy Phd Jobs (NOW HIRING)

Nextracker

Sr. Principal Engineer

Fremont, CA · On-site +1

PhD in Optimization, Operations Research, Applied Mathematics, Industrial Engineering, or a closely ... At Nextpower, we are driving the global energy transition with an integrated clean energy ...

QCi

Senior Engineer, Quantum Algorithms

Hoboken, NJ · On-site

Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics. * Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks. * Familiarity with Open Quantum ...

Nextpower

Sr. Principal Engineer

Fremont, CA · On-site

PhD in Optimization, Operations Research, Applied Mathematics, Industrial Engineering, or a closely ... At Nextpower, we are driving the global energy transition with an integrated clean energy ...

Oxy

AI Optimization Engineer

Houston, TX · On-site

Required : • Master's degree in Engineering, Applied Mathematics, or a related field. • Strong ... Company : Oxy is an international energy company that produces, markets and transports oil and ...

QCi

Advanced degree (MS/PhD) in Computer Science, Physics, or Mathematics. * Experience with classical optimization solvers (e.g., CPLEX, Gurobi) or heuristic frameworks. * Familiarity with Open Quantum ...

Nrel

ML and Optimization Engineer

Golden, CO

... for energy systems research and development. Join the National Laboratory of the Rockies (NLR ... Or, relevant PhD or equivalent relevant education/experience. Complete understanding and wide ...

bp

Midstream Optimization Team Lead

Denver, CO · On-site

$196K - $235K/yr

Finance Group bpx energy, a major oil and gas producer in the United States, leverages its ... Bachelor's degree in Engineering, Mathematics, Computer Science, or related STEM field. * 15 years ...

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Math Optimization Energy Phd information

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$58.8K

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How much do math optimization energy phd jobs pay per year?

As of Jun 6, 2026, the average yearly pay for math optimization energy phd in the United States is $58,837.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,000.00 and $70,000.00 per year, depending on experience, location, and employer.

What is the difference between Math Optimization Energy Phd vs Data Scientist?

AspectMath Optimization Energy PhdData Scientist
Required CredentialsPhD in Mathematics, Optimization, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field
Work EnvironmentResearch-focused, often in energy companies or R&D labsBusiness or tech companies, analytics teams
Industry UsageEnergy, utilities, research institutionsTech, finance, healthcare, retail

The Math Optimization Energy Phd specializes in advanced mathematical models and optimization techniques within the energy sector, often focusing on research and development. In contrast, Data Scientists analyze large datasets to extract insights and support decision-making across various industries. While both roles require strong analytical skills, the Phd role emphasizes theoretical and applied mathematics in energy contexts, whereas Data Scientists focus on data analysis and machine learning applications.

What is a Math Optimization Energy PhD?

A Math Optimization Energy PhD is an advanced doctoral degree focused on applying mathematical optimization techniques to solve complex problems in the energy sector. Students in this field develop mathematical models and algorithms to improve energy systems, such as electricity grids, renewable integration, and resource allocation. The program combines mathematics, computer science, and engineering concepts to address challenges like efficiency, sustainability, and cost in energy production and distribution. Graduates often pursue careers in academia, research institutions, or energy companies, working on innovative solutions for a sustainable energy future.

What types of interdisciplinary collaboration can I expect as a Math Optimization Energy PhD in the energy sector?

As a Math Optimization Energy PhD, you'll frequently work with multidisciplinary teams that include engineers, data scientists, policy analysts, and project managers. Your role typically involves developing mathematical models or algorithms to optimize energy systems, and you'll often need to translate complex results into actionable insights for colleagues with varying technical backgrounds. Collaboration may occur through regular meetings, joint research projects, and cross-functional workshops, making strong communication and teamwork skills essential. This environment offers opportunities to contribute directly to impactful projects, such as improving grid efficiency or advancing renewable energy integration.

What are the key skills and qualifications needed to thrive as a Math Optimization Energy PhD, and why are they important?

To thrive as a Math Optimization Energy PhD, you need advanced expertise in mathematical modeling, optimization techniques, and a deep understanding of energy systems, typically supported by a doctoral degree in a relevant field. Familiarity with optimization software (such as Gurobi or CPLEX), programming languages like Python or MATLAB, and experience with energy simulation tools are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills set standout candidates apart. These skills are crucial for developing innovative solutions to complex energy challenges and effectively collaborating within multidisciplinary teams.
Sr. Principal Engineer

Sr. Principal Engineer

Nextracker

Fremont, CA • On-site, Remote

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 29 days ago

Job description

Job Description:

We are seeking a Senior Principal Engineer to lead advanced AIdriven optimization initiatives for complex logistics systems. This role is responsible for designing, modeling, and solving largescale optimization problems that directly impact operational efficiency, cost, and scalability across logistics and supplychain applications.

The ideal candidate combines deep academic rigor in optimization with handson industrial implementation experience, and can act as both a technical authority and architect for optimizationbased AI solutions.

Key Responsibilities

  • Lead the design and implementation of optimization models for largescale logistics and supplychain problems (e.g., routing, scheduling, network design, capacity planning).

  • Develop and maintain optimization formulations using Pythonbased modeling frameworks such as: Gurobi / GurobiPy Pyomo

  • Select, implement, and tune appropriate optimization algorithms, including: Linear Programming (LP) MixedInteger Linear Programming (MILP) NonLinear Programming (NLP)

  • Translate complex realworld logistics constraints into mathematically rigorous and computationally efficient models.

  • Collaborate with AI, data science, and system engineering teams to integrate optimization engines into production AI platforms.

  • Evaluate solver performance and scalability; optimize model performance for realtime or nearrealtime decisionmaking.

  • Provide technical leadership, mentoring, and design reviews for optimization engineers and researchers.

Required Qualifications

  • PhD in Optimization, Operations Research, Applied Mathematics, Industrial Engineering, or a closely related field.

  • Deep expertise in mathematical optimization modeling and algorithmic design.

  • Strong handson experience with: Gurobi / GurobiPy Pyomo

  • Proven knowledge of and practical experience with: LP, MILP, and NLP formulations Solver behavior, numerical stability, and computational complexity

  • Strong understanding of logistics and supplychain optimization problems

  • Advanced Python programming skills for model development and integration.

Preferred (NicetoHave) Qualifications

  • Experience applying optimization techniques in autonomous systems, including: Motion planning Trajectory optimization Autonomous vehicle or robotics applications

  • Familiarity with hybrid approaches combining optimization and machine learning.

  • Experience deploying optimizationbased decision engines in production environments.

Nextpoweroffers a comprehensive benefits package. We provide health care coverage, dental and vision, 401(K) participation including company matching, company paid holidays with unlimited paid time off, generous discretionary company bonuses, life and disability protection and more. Employees in certain positions may be eligible for stock compensation. All plans are in accordance with relevant plan documents. For more information onNextpower's benefits please view our company website atwww.nextpower.com.Pay is based on market location and may vary based on factors including experience, skills, education and other job-related reasons. The annual salary range for this position is $275,000-$300,00.

At Nextpower, we are driving the global energy transition with an integrated clean energy technology platform that combines intelligent structural, electrical, and digital solutions for utility-scale power plants. Our comprehensive portfolio enables faster project delivery, higher performance, and greater reliability, helping our customers capture the full value of solar power. Our talented worldwide teams are redefining how solar power plants are designed, built, and operated every day with smart technology, data-driven insights, and advanced automation. Together, we're building the foundation for the world's next generation of clean energy infrastructure.

Nextpower is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

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