Thank you for your interest in joining our group. Please read this page before writing to me. It will help you decide whether we are a good fit, and it will help me respond to you.
Is our group right for you?
We are primarily a theory and computation group. We do carry out some experiments, but they are not our mainstay, and most of our work involves developing models, analyzing data, and writing code. If you are primarily an experimentalist, we may not be a good fit for you at present. Our current research is described on our research page.
Prospective PhD students
I cannot admit students directly. To join the group, you must first be admitted to one of Berkeley’s PhD programs. Our group is affiliated with:
- Chemical and Biomolecular Engineering
- Computational Biology
- Neuroscience (Helen Wills Neuroscience Institute)
- Biophysics
- Vision Science (School of Optometry)
If you think you would be a good fit for our group, please email me at kshekhar@berkeley.edu with your CV and a short statement of your research interests.
Prospective postdocs
I am always glad to hear from postdoctoral candidates whose interests overlap with ours, particularly those with strong quantitative training. Please email me at kshekhar@berkeley.edu with your CV, a short statement describing your research interests and how they connect to our work, and the names of two or three references. I am also happy to support strong candidates applying for independent postdoctoral fellowships.
Undergraduates
I can advise only undergraduates currently enrolled at UC Berkeley who are strongly motivated by the areas of our research. I am unable to advise students remotely, and I do not have the capacity to host summer or visiting internships.
A note on email
Because of the large volume of email I receive, I am unable to respond to everyone individually. My apologies if I have not replied to you; please feel free to write again.
Please note, however, that I may also not respond if I do not sense a strong intellectual fit. Many of the emails I receive are generic and appear to be written by AI tools. I am much more likely to respond if you have taken the time to read our papers and your email shows that you have engaged with them: tell me what you found interesting, what questions they raised for you, and how your own background would help us address them. Please also tell me which technical methods and tools you are familiar with, whether in theory, computation, or data analysis, and how they would make you a good fit for our work.
I do not expect you to know everything in advance. But I do need to sense a genuine commitment to thinking carefully and deeply about science.