In anticipation of NIH funding to study xenobiotic metabolism and metabolite reactivity, our group is currently recruiting new members. At this time (March 2016), we are looking to add two PhD students and one postdoctoral fellow.
We are looking to train scientific leaders, capable of innovative computational research at the intersection of biology, chemistry, and medicine.
- The strongest applicants will already have experience with both computational science (e.g. molecular dynamics, neural networks, machine learning) and xenobiotic metabolism (e.g. chemical modeling, P450 metabolism, drug metabolism). We will consider applicants that have proficiency in computational research only if they are strongly motivated to learn the relevant biology and chemistry.
- Strong technical writing skills are required. Ideally, especially for postdoctoral applicants, this should be evident in a track record of well-written, peer reviewed papers.
- Experience in computational research is required. Ideally, especially for postdoctoral applicants, this should be evident in a track record of successful research projects. Our group uses, mainly, neural networks in a Python programing environment, though we are expanding into molecular dynamics and biophysical modeling.
- Ideal applicants will be aiming for careers in academic research, but we will consider applicants looking for careers in industry.
- Postdoctoral applicants should be highly motivated and ready to work independently. Creativity and drive is highly valued. There will be substantial opportunities to manage other researchers and apply for funding (e.g. K awards). The goal should be to develop into an independent researcher with promising research program.
- Specific responsibilities and research projects will be tuned to the career goals, technical strengths, and interests of the applicant.
Interested applicants should send a CV, two references, and a brief career goal statement to Prof. Swamidass. His email is his last name at gmail dot com.