The selected applicant will contribute to ongoing research in the Burke lab by building and writing parts of the Multi Scale Informatics code, which combines theoretical and experimental data to create optimized kinetics models for various combustion and other chemically reacting systems. Using these models, one can address a variety of real world problems, which include improving vehicle emissions, effectively destroying chemical/biological weapons, and developing novel engine designs. The selected student will develop code for mining, categorizing, and restructuring data from various online databases and creating visualization and other post-processing functionalities. In addition to computational work, the student will have the opportunity to assist in ongoing experimental work in the lab.
Lab: Data-Enabled Science and Engineering for Energy and the Environment
Direct Supervisor: Michael P. Burke
Position Dates: 8-10 Weeks, Summer 2018
Hours per Week: 40
Paid Position: Yes
Positions available: 1
Qualifications: The student should be familiar with, but preferably proficient in, python or another equivalent language. The student should also ideally have some minimal computational or modeling experience.
Eligibility: Freshman, Sophomore, Junior, Senior; SEAS only