Working at MIT offers opportunities, an environment, a culture - and benefits - that just aren't found together anywhere else. If you're curious, motivated, want to be part of a unique community, and help shape the future - then take a look at this opportunity.
POSTDOCTORAL ASSOCIATE , MIT Energy Initiative (MITEI) , to work on a project on advancing systems modeling tools related to power sector investment planning under uncertainty through advanced optimization. The project is primarily supported by the Low-Carbon Energy Centers (LCEC) on electric power systems and will develop optimization models and methods to study the cost-effectiveness of investments in generation, storage, and transmission in the bulk power sector under uncertain technology and policy futures, while explicitly considering the flexibility requirements of future renewables-dominated power systems. Will study the role of emerging energy storage technologies in future low-carbon electricity systems under uncertain technology (e.g., storage cost and performance) and policy (e.g., carbon policy, market structures) futures. Responsibilities include developing/improving computationally efficient power system optimization models; using the developed models to provide policy-relevant recommendations through studying applications pertaining to the role of existing and new natural gas assets and emerging technologies (e.g., battery storage); presenting research results in sponsor meetings and center workshops; and publishing papers in international conferences and peer-reviewed journals. The position offers opportunities for working closely with MIT researchers and involvement in MITEI's LCEC.
Job Requirements REQUIRED : Ph.D. in an engineering discipline; demonstrated background in energy systems (e.g., energy engineering, electrical engineering, chemical engineering, or industrial engineering); excellent communication skills, including spoken and written English fluency; independent research skills; and ability to prioritize work to meet deadlines. The ideal candidate possesses expertise and relevant track record in formulating and solving optimization models; working knowledge of power systems and grid technologies; and experience handling large data sets and with at least one of the following: Julia, GAMS, Python, and/or MATLAB. Job #18935
In addition to applying online via the MIT website with a full CV and research statement, applicants are asked to submit these materials plus two letters of recommendation to Dr. Dharik Mallapragada at email@example.com.
This is a one-year position with possibility of renewal depending on the progress achieved and continued funding.
Internal Number: 18935
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