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Sandia National Laboratories · 3 hours ago

Senior/Principal Computer Scientist - Optimization & Operations Researcher, Hybrid

Albuquerque, NM

Full-time

Hybrid

Senior Level, Lead/Staff

$118K/yr - $236K/yr

5+ years exp

Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. They are seeking an innovative Computer Science- Optimization and Operations Researcher to lead R&D efforts, driving impact by designing optimization algorithms and applying mathematical modeling to critical domains.

GovernmentInformation TechnologyNational Security

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

Designing and implementing novel optimization algorithms and advanced operations research methods

Applying mathematical modeling to critical domains, including power grid modeling and analysis, cybersecurity, process systems engineering, and national security logistics

Developing robust, scalable software tools that empower mission partners and advance the capabilities of the global scientific community

Collaborating across disciplines to bridge the gap between theoretical mathematics and practical, real-world applications and solutions

Sharing results via high-impact publications and presentations to funding agencies, stakeholders, and the broader research community

Qualification

Optimization AlgorithmsOperations Research MethodsPythonMixed-Integer ProgrammingStochastic ProgrammingNonlinear ProgrammingSoftware EngineeringHigh-Performance ComputingResearch Track RecordDomain ExpertiseSponsor EngagementTeam LeadershipCommunication Skills

Required

A Bachelor's degree in a relevant discipline and five (5) years of directly relevant experience, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development

Ability to obtain and maintain a DOE Q clearance

Preferred

Graduate degree in Computer Science or a highly related field where an independent research project was a graduation requirement (e.g., independent project, thesis, or dissertation)

Strong verbal and written communication skills, ability to work effectively in multidisciplinary teams, and a passion to improve and expand technical skills

A PhD in Applied Mathematics, Computer Science, Engineering, Operations Research, or a closely related quantitative field, along with a Bachelor's degree in a STEM discipline

Demonstrated experience with major optimization paradigms, including Linear Programming (LP), Mixed-Integer Programming (MIP), Stochastic Programming, and/or Nonlinear Programming (NLP), or advanced Constraint Programming

Proficiency in Python and experience with modern software development and engineering practices, including version control (e.g., GitLab), testing, and collaborative coding workflows

A record of peer-reviewed publications and presentations at major scientific conferences demonstrating research leadership, combined with a history of successful project delivery, implementation, and/or technology transfer

Proven experience as a constructive and inclusive team lead or member within a diverse, interdisciplinary research environment, demonstrating responsibility and responsiveness in project execution

Expertise in theoretical and computational aspects of Mixed Integer Programming (MIP), Stochastic Programming, and other algorithms for discrete optimization

Applied experience in one or more critical areas: process systems engineering, dynamic optimization and control, and/or electric grid modeling and analysis

Competence and familiarity with high-performance scientific computing, experience leveraging optimization solvers (e.g., CPLEX, Gurobi, and Ipopt) and modeling environments (e.g., Pyomo and JuMP), and proficiency in programming languages for scientific computing (e.g., C/C++ and Julia). A track record of contributing to open-source research software and leveraging high-performance computing environments to solve complex optimization problems

Proven ability to engage effectively with program managers, funding agencies, and other stakeholders to align research goals with mission priorities