Texas public universities to partner for data science camp
With a high demand for a data science workforce that has a broad understanding of conventional energy, five major Texas public universities, including UH, are setting up a path to the industry.
The University will be leading a project in collaboration with UH-Downtown, UH-Victoria, UH-Clear Lake and Sam Houston State University. Next summer, all five schools, and several energy industry partners will train students in a five-week data science camp aimed at transitioning to cleaner energy.
“Students will get useful training on basics of data science as well as topics on geoscience and public policy, all under the theme of energy and energy transition,” said principal investigator for the program Mikyoung Jun. “The goal here is to prepare them to be a future workforce for the industry and community.”
Jun and 11 other faculty members from the five universities will serve as senior personnel. The project’s faculty affiliates will also teach and mentor student participants.
Energy industry partners for the project include companies like ConocoPhillips, Schlumberger, Fugro, Quantico Energy Solutions, Shell and Xecta Web Technologies.
“We have a website to inform people about our program as well as to take applications,” Jun said. “But we plan to utilize social media and other available channels to advertise. We have 40 spots available for each year, and so there may be some selection process depending on how many applications we get.”
The program starts with a five-week summer boot camp. After, students will take more advanced courses on some of the topics in the fall at their home institution. They would then participate in team research projects with real data provided by the industry partners in the spring. The end goal is for students to get a summer internship the following summer, concluding the program.
The program is open to any major and no prerequisites are required. Both undergraduate and graduate students can apply.
“Any student interested in learning about data science and how data science techniques can be applied to various energy-related problems would be welcome,” Jun said.