The MIT Energy Initiative at Massachusetts Institute of Technology invites applications for a Post-Doctoral position in the area of energy systems analysis.

This project develops and deploys a modular tool (SESAME) to perform systems-level life cycle and techno-economic analysis for major energy and industry related pathways for strategic decision-making. The ideal candidate for this industry collaborative project should have expertise and a relevant track record in one or more of i) process modeling, ii) life cycle analysis, iii) techno economic assessment and iv) modeling and optimization (ideally software development). Demonstrated knowledge of using commercial process modeling software such as Aspen Plus programming languages such as MATLAB or Python is required. The successful candidate will have the opportunity to interact and work closely with researchers at MIT and involve in MIT Energy Initiative’s Low-Carbon Energy Centers.

Applicants must have a PhD (or equivalent experience and/or qualifications) in a subject pertinent to the research area. Candidates are expected to regularly present research results in sponsor meetings and center workshops, publish papers in international conferences and in peer-reviewed journals.

Excellent communication skills, being able to produce with minimal supervision and prioritize work to meet deadlines are essential. All applicants must be fluent in spoken and written English. 

To apply for this opportunity, applicants should send their application package (full CV and a research statement) to Dr. Emre Gençer (Research Scientist at MIT Energy Initiative, [log in to unmask]). The applicants should also arrange to have at least two letters of recommendation send to the above email address. The project will be based at the Massachusetts Institute of Technology campus in Cambridge, MA.  For further information on the group and related projects, please contact Dr. Gençer.

Recent publications:

Sustainable energy system analysis modeling environment: Analyzing life cycle emissions of the energy transition

Parametric modeling of life cycle greenhouse gas emissions from photovoltaic power

Insights Into Future Mobility