Data analytics, automation, and multi-scale/multi-physics modeling

The Burke lab of Columbia University focuses on addressing scientific challenges in the field of combustion through a combination of novel experimental and computational strategies that employ high levels of automation, data analytics methods, and multi-scale/multi-physics models.

We are currently seeking an undergraduate research assistant to work on a self-contained project(s) that will make valuable contributions to one (or both) of the following areas of ongoing research.  We primarily seek students to contribute to the first topic below, though an interested student may also have the opportunity to contribute to the second topic as well.

  1. Multi-Scale Informatics Code (MSI): Combines theoretical and experimental data to create optimized kinetics models for various combustion 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. Projects related to the MSI code consist of the following:
    1. Writing a program in Python to parse journal papers to find and export data in a structured format.
    2. Writing a program or implement existing Python packages to recognize and easily convert units for MSI input data.
    3. Assisting in writing additional modules for the MSI code in order to incorporate additional combustion simulations
    4. Updating project GitHub, including addition of documentation for MSI software
    5. Writing test scripts for MSI code
       
  2. Jet-Stirred Reactor Experiment: A combustion experiment that consists of a continuous flow reactor (within which combustion takes place), along with various other plumbing components such as valves, mass flow controllers, pressure sensors, pressure regulators, and several analytical devices. The long-term goal is to automate this experiment and couple it with the MSI code. Projects related to this experimental work consist of the following:
     
    1. Writing Python code to control mass-flow-controllers for gas flow, including error handling procedures
       
    2. Writing Python code for temperature control
       
    3. Writing Python code for controlling analysis devices, including NOx analyzer and gas chromatograph
       
    4. Building framework in Python for controlling all instruments via single interface
       
    5. Assisting with experimental operations and troubleshooting as necessary.

We are willing to work with the selected applicant to tailor the project to their individual research interests for a fun and engaging summer.

Direct Supervisor: Prof. Michael Burke (as well as his PhD. Students)

Position Dates: 8-10 weeks

Hours per week: 40

Paid Position: Yes

Credit: No

Positions available: 1

 

Qualifications: Student should be familiar with, but preferably proficient in, Python (or an equivalent language). The student would also ideally have some computational or modeling experience and, as relevant, some experience in electronics and mechanical design.

Eligibility: Freshman, Sophomore, Junior, Senior, (SEAS only)

 

Contact: To express interest, inquire about the position, and/or apply, please email Prof. Michael Burke (mpburke@columbia.edu) and cc Carly LaGrotta (c.lagrotta@columbia.edu) with the subject line “Summer Research Position”.