Summer Undergraduate On-line Research
in Computational Chemistry and Computational Science
Help us grow an on-line community in which undergraduate students, graduate students, and faculty use computation to solve important problems in modern chemistry.
Summer 2015 Opportunities
We are looking for motivated undergraduate students who:
- Are currently sophomores or juniors majoring in chemistry, computer science, or related field
- Would like to work remotely on-line (from any location with broadband internet)
- Are interested in either computational chemistry, machine learning, or modern web programming
- Are comfortable with computers and motivated to become computational experts
Summer stipends available, with preference given to students who meet one or more of the following criteria
- Are experienced with one of the following:
- Electronic structure computations in Gaussian, Gammes, Ampac, PSI4 or similar program
- Machine learning
- C++, Matlab, or HTML5 programming
- Parallel programming or use of supercomputing centers
- Have a particular reason (family care giver, physical limitations, etc) to prefer to work on-line for the summer
Application materials include the Summer 2015 application form and two letters of recommendation.
- Download Application Form [Microsoft Word]
Submitting your application by email
Applications must be submitted electronically by e-mailing and attaching the application form. Letters of recommendation may be emailed separately with the applicant's name in the subject line.
Applications will be considered and students admitted on a continual basis. In order to receive full consideration for your application, please submit before April 17, 2015.
The following are projects that will be active in the Summer 2015. We are also open to additional project ideas.
Molecular Similarity in Quantum Chemistry
Molecules consist of fragments (functional groups) that behave similarly in similar environments. This project is adapting approaches from machine learning to take advantage of such "molecular similarity" in electronic structure theory. The general approach is to: - Use high-level (computationally expensive) methods to generate a database with detailed data on the electronic structure of functional groups in various molecular environments - Use machine learning to develop a low-level (computationally inexpensive) model that reproduces the high-level data This project is open to both chemists and computer science students.
Organic Semiconductors Containing Phosphorous
2-Aryl-1,3-Benzothiaphospholes developed in the Noonan lab.
Conjugated polymers [http://en.wikipedia.org/wiki/Conductive_polymer] are plastic materials that can be used to build electronic devices. While such polymers consist primarily of first row elements (H,C,N, and O), incorporation of sulfur (S) leads to polythiopene, which is among the most promising material for use in transistors and solar cells. Kevin Noonan's group at CMU [http://www.chem.cmu.edu/faculty/noonan.html] has recently incorporated phosphorous (P) into highly-conjugated molecules. In collaboration with the Noonan group, this project is using computation to explore the properties of this new class of P-containing conjugated polymers.
Dyes for Biological Imaging
In collaboration with the Molecular Bio Imaging Center [http://www.mbic.cmu.edu/], we are developing organic dyes that can be used to monitor the location of molecules in living cells. One such class of dyes is fluorogens, which fluoresce only when bound to a protein. Another class of dyes detects the presence of Potassium ions and can be used to monitor nerve action. This project uses quantum chemical computations to screen potential dyes and optimize properties of importance to imaging.
Infrastructure for On-line Science
- Attaching "provenance" to all data generated by the projects, such that we know what has been done and what still needs to be done
- Integrating the provenance management system into an on-line notebook systems, so that we have a better trace of the scientific goals, process and outcomes
- Creating software tools to allow automation of routine tasks
Providing an on-line environment that supports distributed work in computational science is an important challenge of this project. We are developing software tools to manage research projects by:
This project is particularly open to computer science students interested in HTML5 programming.