Welcome to the
A Research Group in Theoretical Chemistry
Developing classical molecular dynamics (MD) simulations that provide quantum expectation values for condensed phase systems.
Applying powerful machine learning (ML) tools, such as artificial neural networks, to push the boundaries of molecular simulations.
Using simulations to investigate fascinating problems, such as chemical reactions on water surfaces or stability of exotic phases of matter.
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Three who know podcast - Barak explains what supersolids are (in Hebrew)
Several positions are available at all levels (Postdoc, PhD, MSc, undergratuate interns).
If you are interested in discovering how machine learning can improve molecular simulations, how to study quantum condensed phase systems using classical simulations, or how to apply these tools to exotic quantum materials or chemical reactions on water surfaces - get in touch!
To apply, please send your CV and a short description of your research interests to Barak.