We usually have open research opportunities in the group for excellent and motivated graduate students. If this fits your description and you think you may want to join us we would love to hear from you
- If you are a Ph.D student at Columbia University in Materials Science, Applied Physics, Applied Mathematics or any department in SEAS, then please contact Professor Billinge (firstname.lastname@example.org).
- If you are a Ph.D student at Columbia University in the Physics or Chemistry Departments, or in some related discipline, then please contact Professor Billinge (email@example.com).
- If you would like to study for your Ph.D in the group but you are not already admitted into the PhD program at Columbia then you need to apply either for the Materials Science PhD program or the Applied Physics PhD program (http://www.apam.columbia.edu). Ph.D students are generally admitted beginning in the fall semester and the deadline for applications is usually around December of the previous year. Start the process early. You will need a valid GRE score, and TOEFL if you are applying from a non-english-speaking country.
There are multiple opportunities in the group to learn how to understand atomic arrangements on the nanoscale (a billionth of a meter) and the relationship of these to properties of those materials. In the group we study a wide range of materials, from the applied (HIV pharmaceuticals) to the pure science (understanding novel magnetic and superconducting properties of exotic quantum materials with no known applications). We also develop new experimental and computational methods for analyzing nanostructure.
Depending on your interests there are likely to be various options available to work on. What all the projects have in common is the use of computers to carry out advanced data analysis. No prior experience is required for these positions, but for success it is necessary that you have an interest in learning how to use advanced computing, including for example, machine learning, AI and other statistical methods to answer real scientific questions. Experience in these areas, and in programming in Python, is even better.
- PhD research
Fully supported on an RA or TA of Fellowship
Background in at least one of the following fields is requested:
- No particular experience required but a keen interest in using, or learning to use, computers to analyze data to answer interesting scientific questions. Experience in coding in python is a plus as is any experience with data analysis, including AI, and machine learning.
Status: This position is currently OPEN.
Start Date: Rolling
Posting Date: Jan 1, 2020
Contact: Please contact Prof. Simon Billinge at sb2896ATcolumbia.edu.