Pacific Northwest National Laboratory PhD Intern - Numerical Optimization in SEATTLE, Washington

Organization and Job ID

Job ID: 306196

Directorate: Energy and Environment

Division: Electricity Infrastructure & Buildings

Group: Advanced Controls

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Job Description

The objective of this internship is to develop and implement parallel solvers for linear mixed integer programming models used for day-ahead market unit commitment. The plan is to

1.Explore cutting plan, branch-and-bound scheme, Lagrangian relaxation, and decomposition techniques for solving security constrained unit commitment problems.

2.Develop, implement and test algorithms in HIPPO software package (Python).

3.Implement the tested methods to HPC.

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Minimum Qualifications

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

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Preferred Qualifications

Linear and mixed integer optimization, numerical optimization, Python, GUROBI, Numerical libraries e.g., GNU GSL, Armadillo

Specialized in Operations Research, Computer Science, Applied Math with emphasis in optimization.

3.5 GPA or higher is preferred

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Equal Employment Opportunity

PNNL is an Equal Opportunity/Affirmative Action Employer that is committed to hiring a diverse, talented workforce. EOE Disability/Vet/M/F/Sexual Orientation/Gender Identity. Staff at PNNL must be able to demonstrate the legal right to work in the United States.

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Directorate: Energy & Environment

Job Category: Master's and PhD Level Internships

Group: Advanced Controls

Opening Date: 2017-01-11

Closing Date: 2017-03-12