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, COMBUSTION, Aeronautics and Astronautics-Laboratory for Aviation and the Environment (LAE), to contribute to research in combustion and aircraft engine modeling. The aim of which is to investigate the emissions and performance characteristics of current and future engine, combustor, and aviation fuel technologies. Research activities will include using chemical kinetic simulation software to develop low-dimensional models for gas turbine combustors; evaluating combustor and engine cycle models based on experimental data; applying state-of-the-science modeling techniques such as machine learning to improve modeling capabilities; developing and evaluating chemical kinetic models for nonconventional aviation fuels; modeling the effectiveness of technologies for reducing NOx and soot emissions; and coupling combustion and engine cycle models to atmospheric modeling tools.
REQUIRED: Ph.D./equivalent degree in mechanical engineering, aerospace engineering, chemical engineering, or related field; background in combustion, chemical kinetic modeling, and/or aerospace propulsion (broadly defined); willingess to expand focus to cover several of the topics outlined in the scope of work; excellent analytical, problem-solving, documentation, technical writing, organizational, and interpersonal skills; proficiency in English communication; ability to both work independently and contribute in a multidisciplinary team setting, prioritize, perform multiple tasks in a dynamic environment, and execute detailed technical protocols meticulously; and self-motivation. Preference will be given to candidates with a focus on gas turbine combustion and/or the formation of pollutants including NOx and soot. PREFERRED: programming experience in Python, Julia, or C++ for developing modeling tools and with the application of machine learning and deep learning methods; experience using combustion modeling platforms such as Cantera; ability to work in Linux-based high-performance computing environments; and a publication record in the fields noted above or related fields. Job 19458
Application material should include a C.V., a cover letter, and contact information for three references.
The appointment will be for one year with the possibility of renewal pending satisfactory performance and funding availability.