Lab members
The Meisner Lab works on population genetics, statistical genetics, and scientific computing.
Current team
Principal Investigator · Assistant Professor
Jonas develops statistical and machine-learning methods for population and statistical genetics, with a focus on accurate inference from large, diverse, and low-depth genetic datasets.
His current work focuses on hapla and fastmixture, with swerge in development. Earlier tools include PCAngsd, HaploNet, and emu.
Postdoctoral Researcher
Zilong loves to develop highly efficient methods and algorithms in population and statistical genetics while playing around with his Emacs configuration.
Research Assistant
Lisa has recently started in the lab as research assistant and will soon start her PhD in the lab working on developing scalable methods in population and statistical genetics.
MSc student
Daniël is doing his Master's thesis in the lab working on utilizing autoencoders for ancestry estimation.