Computational Training Class

The computational training class is an initiative to strengthen and expand a year-round hybrid research program aimed at preparing and increasing the number of community college (CC) students in STEM PhD programs.

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The long-term goal of this proposal is to develop a sustainable and practical year-round innovative, collaborative research program between partnering UC R1 institutions and geographically distinct California CCs (Sacramento City College, Los Medanos College, Cosumnes River College, American River College, Folsom Lake College, Long Beach City College, Southwestern College and West Los Angeles College) which can later be broadly adapted by other STEM departments across the entire UC system.

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In stark contrast to current research opportunities at the CCs, this program will expose and enable CC students, directly from their CCs, to use and apply cutting-edge computational tools including machine learning (ML), artificial intelligence (AI), quantum mechanical calculations (QM), molecular dynamic simulations (MD), qualitative analysis (QA), and data science (DS) methods for cutting edge research.

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Program Objectives: ​

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(1) Match students from community colleges across the state with remote computational chemistry and chemistry education research projects during the school year.

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(2) Invite students to conduct in-person research at UCLA during the summer.

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(3) Facilitate a pipeline of research-ready STEM majors transfer students to UCLA.

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(4) Support community college chemistry faculty to access research and educational resources.

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The Gutierrez group have proven success working with community college students/faculty and lead cutting-edge research programs designed to be fully accessible to remote researchers in CC students in STEM and, in parallel, prepare them to transfer and thrive at R1 institutions.

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