OPPORTUNITIES
Postdoc Opportunities:
Although we are not actively looking for new postdocs, exceptional candidates will be considered. Candidates should send their CV and a description of their research interests by email. The following projects are listed in order of priority for hiring.
Multiscale Responsive Kinetic Modeling (MsRKM)
MsRKM is a kinetic modeling framework that bridges simulations and experiments–integrating insights and data from both–to model equilibrium, steady state and non-equilibrium processes. It is currently focused on modeling electrochemically-driven transport, so well suited to channels and transporters–one of our most exciting projects! This work will combine method development with application to ion channels and transporters (to start…so many more processes we can study in time). The ideal candidate will have exposure to kinetic modeling (e.g., microkinetic modeling, systems bio modeling, MC kinetic modeling, or Markov state models), simulations, enhanced sampling, and machine learning, but some learning on the job is expected. Experience with channels and transporters is a plus.
Multiscale Simulations for Methane Mitigation
Probing the roles of membranes in the uptake, delivery and oxidation of methane by pMMO (see Team Methane). This work will involve large scale simulations, enhanced sampling, and potentially multiscale methods (reactive MD and/or QM/MM). Experience with MD and some of these methods is expected, with additional learning on the job supported. Interests in machine learning welcome.
Protein Targeting to Lipid Droplets
We are characterizing the mechanisms by which proteins target lipid droplets specifically and in response to cellular conditions. In effect, we are hoping to learn the regulation mechanisms of the lipid droplet proteome. To do so, we are using all-atom and CG simulations. We are also developing new methods to characterize these processes. Experience with MD and enthusiasm for understanding biomembranes expected, with additional learning on the job supported. Interests in kinetic modeling, systems biology, and machine learning welcome.