We are looking for self-motivated students who are interested in researches in computational drug discovery. Students with coding experiences (especially C++ and Python) or knowledge of proteins are highly encouraged to apply. For consideration, please send your CV (with a list of references) and a cover letter to Dr. Paul Xie at paulxie@uga.edu. For guaranteed review, please contact Dr. Paul Xie directly – direct applications to the graduate school without prior contact are not advised.
We are looking for self-motivated undergraduate students 1. Who know programming; or 2. Who would like to study biomedical problems with computational approaches. The cost of bringing a new drug to the market has been increasing dramatically; therefore, computational drug design has become one of the top interests of industry and academy. We currently have several collaborative research projects to identify or modify drug candidates for diseases (e.g. cancers) and to reveal the mechanisms of protein-protein/compound interactions, which cause diseases. Students will learn the knowledge of the relationship between protein 3D structures and their functions, gain hands-on experience in operating state-of-the-art software in virtual drug discovery, and publish the results on peer-reviewed journals by participating in this research project. The experiences of computational drug discovery will be a big plus for your academic or industrial career. Interested students please contact Dr. Paul Xie by email: paulxie@uga.edu Every semester, we look for 2-3 undergraduate students who are interested in virtual drug discovery team or programming team. We have a training course which will be held in the beginning of every semester; therefore, students who are interested in joining us please contact us by every August 31st, January 15th, and May 31st in order to take the training course. But we will accept students who are interested in programming team anytime in the semester. Besides, the students who would like to do the research in this lab need to commit at least 10 hours per week and attend the weekly lab meeting.