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Math Optimization Energy Phd Jobs (NOW HIRING)

Optimization Engineer

$217K - $237K/yr

The Optimization Engineer will provide technical leadership in the creation of a programmatic ... mathematical foundation. > * Strong knowledge of energy systems, wholesale power markets, or power ...

Optimization Engineer

Charleston, WV · Remote

$217K - $237K/yr

The Optimization Engineer will provide technical leadership in the creation of a programmatic ... mathematical foundation. * Strong knowledge of energy systems, wholesale power markets, or power ...

... Mathematics, or a related quantitative field with 3+ years of hands-on industry experience, or a PhD in a related field. • Proven track record of taking optimization solutions from problem ...

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Math Optimization Energy Phd information

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$22.5K

$58.8K

$94.5K

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.
PhD Intern - Computing Cost Modeling and Optimization

PhD Intern - Computing Cost Modeling and Optimization

Pacific Northwest National Laboratory

Pierre, SD • On-site

$16.75 - $21.75/hr

Internship

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.

Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The Physical and Computational Sciences Directorate's (PCSD's) strengths in experimental, computational, and theoretical chemistry and materials science, together with our advanced computing, applied mathematics and data science capabilities, are central to the discovery mission we embrace at PNNL. But our most important resource is our people-experts across the range of scientific disciplines who team together to take on the biggest scientific challenges of our time.?

The Advanced Computing, Mathematics, and Data Division (ACMDD) focuses on basic and applied computing research encompassing artificial intelligence,?applied mathematics, computing technologies, and data and computational engineering. Our scientists and engineers apply end-to-end co-design principles to advance future energy-efficient computing systems and design the next generation of algorithms to analyze, model, understand, and control the behavior of complex systems in science, energy, and national security.

Responsibilities

Realizing the potential for science to leverage on-demand cloud scaling and resource diversity requires the ability to control and manage costs. Scientists must have the ability to request SLO constraints with respect to a job's cost. Job orchestrators must be able to schedule task parallelism, manage data objects, select compute instances, and assign storage resources while also tracking costs and ensuring they stay within budgets.

Although cloud vendors provide cost calculators, they provide no ability to specify cost within a SLO constraint for specific jobs. The fundamental problems are that billing data is delayed, many services bill asynchronously, jobs may create downstream resources, charges for shared resources (network, storage, logging) accrue separately, and the ability to specify resource limits is constrained only to particular and local services. It is especially difficult to estimate charges for a distributed set of resources or for agentic workflows that generate dynamic or unpredictable tasks.

PNNL's Future Computing Technologies group seeks an accomplished PhD Intern to explore methods for the characterization and modeling workflow resource usage and cost accumulation within the cloud. Relevant research topics include:

  • Developing job resource telemetry, cost introspection, modeling, and prediction, to reason about expected vs. actual SLO cost.Cross-platform job control mechanisms that enable appropriate alerts as the job progresses, soft landings through checkpointing, and hard stops if necessary.
  • Optimized job execution policies adapted to and reinforced by the cost profile and reasoning

The successful applicant will work within the Future Computing Technologies group and have demonstrated expertise in a topic closely related to performance modeling and scientific workloads. The researcher should be creative, self-motivated, and ready to publish at top-tier venues.

Qualifications

Minimum Qualifications:

  • Candidates must be currently enrolled/matriculated in a PhD program at an accredited college.
  • Minimum GPA of 3.0 is required.

Preferred Qualifications:

  • Pursuing a degree in computer science, data science, or related field.
  • Familiar with topics such as distributed and continuum computing, vector databases, performance modeling, storage and memory systems, etc.

Hazardous Working Conditions/Environment

Not Applicable

Testing Designated Position

This is not a Testing Designated Position (TDP).

About PNNL

Pacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!

At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State-the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab's campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.

Commitment to Excellence and Equal Employment Opportunity

Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.

Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.

We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov .

Drug Free Workplace

PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.

Security, Credentialing, and Eligibility Requirements

As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.

For foreign national candidates:

If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.

Mandatory Requirements

Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a "country of risk" without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Rockstar Rewards

Regular Hourly:

Employees are offered an employee assistance program and business travel insurance. Employees are eligible for the company funded pension plan and 401k savings plan, once eligibility requirements are met.

Temporary Hourly:

Employees are offered an employee assistance program and business travel insurance.

Click Here For Rockstar Rewards (https://careers.pnnl.gov/rockstar-rewards)

Notice to Applicants

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual's relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $24.04/Hr.

Maximum Salary

USD $36.06/Hr.


Pacific Northwest National Laboratory logo

About Pacific Northwest National Laboratory

Sourced by ZipRecruiter

Pacific Northwest National Laboratory (PNNL) is a premier research institution based in Richland, Washington, US. Operated by Battelle Memorial Institute under contract to the US Department of Energy (DOE), it is one of the DOE's seventeen national laboratories. PNNL primarily specializes in fields such as environmental science, energy, nuclear science, and national security. Founded in 1965, the lab has since been committed to its core values of integrity, creativity, collaboration, impact, and courage. Their mission is "to transform the world through courageous discovery and innovation." Notable achievements include significant contributions to projects like the Human Genome Project and the development of grid-friendly appliances.

Industry

Scientific research and development services

Company size

1,001 - 5,000 Employees

Headquarters location

Richland, WA, US

Year founded

1965