Professorship of Multiscale Modeling of Fluid Materials

Prof. Dr. Julija Zavadlav

julija.zavadlav@tum.de
+49 (0)89 289 - 55300
Building Section 1, Room MW 2129

  • hybrid micro/meso/macro simulations
  • molecular modeling of nanostructured materials
  • machine learning

Research

Most scientific phenomena across various fields ranging from life sciences to engineering are multiscale in nature since the associated processes are determined by the interplay of disparate spatial and temporal scales. In our group, we are focusing on tackling such problems with multiscale modeling and simulations, where we merge micro and meso/macroscopic models or methods. These state-of-the-art approaches are essential also from the point of view of computational efficiency. The meso/macroscopic fluid dynamics description may not describe the system with sufficient detail, while the nanoscale description is computationally too demanding. We use many machine learning techniques to advance the field even further. The research interests of our group, therefore, lie at the crossroads between multiscale simulations, machine learning, engineering, and high-performance computing.

Open positions

We are currently looking for Ph.D. candidates and/or postdocs. For more information, see the Ph.D. call.

The Bachelor and Master theses opportunities are always available. The topics can be tailored to the interests of the student but within the research area of the group. If you are interested, please send an email to julija.zavadlav@tum.de.

 

Publications

  • Julija Zavadlav, Georgios Arampatzis, Petros Koumoutsakos, Bayesian selection of  coarse-grained models of liquid water, Sci. Rep. 9, 99
  • Julija Zavadlav, Jurij Sablic, Rudolf Podgornik, Matej Praprotnik, Open-Boundary Molecular Dynamics of a DNA Molecule in a Hybrid Explicit/Implicit Salt Solution,  Biophys. J. 114, 2352-2362
  • Julija Zavadlav, Siewert J. Marrink, Matej Praprotnik, Multiscale Simulation of Protein Hydration Using the SWINGER Dynamical Clustering Algorithm, J. Chem. Theory Comput. 14, 1754-1761
  • Rudolf Podgornik, Julija Zavadlav, Matej Praprotnik,  Molecular Dynamics Simulation of High Density DNA Arrays, Computation 6, 3
  • Julija Zavadlav, Matej Praprotnik, Adaptive resolution simulations coupling atomistic water to dissipative particle dynamics, J. Chem. Phys. 147, 114110
  • Julija Zavadlav, Stas Bevc, Matej Praprotnik, Adaptive resolution simulations of biomolecular systems, Eur. Biophys. J. 46, 821-835
  • Julija Zavadlav, Rudolf Podgornik, Matej Praprotnik, Order and interactions in DNA arrays: Multiscale molecular dynamics simulation, Sci. Rep. 7, 4775-4786
  • Julija Zavadlav, Siewert J. Marrink, Matej Praprotnik, Adaptive resolution simulation of supramolecular water: The concurrent making, breaking, and remaking of water bundles, J. Chem. Theory Comput. 12, 4138-4145
  • Julija Zavadlav, Rudolf Podgornik, Manuel N. Melo, Siewert J. Marrink, Matej Praprotnik, Adaptive resolution simulation of an atomistic DNA molecule in MARTINI salt solution, Eur. Phys. J. Spec. Top. 225, 1595-1607
  • Julija Zavadlav, Rudolf Podgornik, Matej Praprotnik, Adaptive resolution simulation of a DNA molecule in salt solution, J. Chem. Theory Comput. 11, 5035-5044
  • Julija Zavadlav, Manuel N. Melo, Siewert J. Marrink, Matej Praprotnik, Adaptive resolution simulation of polarizable supramolecular coarse-grained water models, J. Chem. Phys. 142, 244118
  • Julija Zavadlav, Manuel N. Melo, Ana V. Cunha, Alex H. de Vries, Siewert J. Marrink, Matej Praprotnik, Adaptive resolution simulation of MARTINI solvents, J. Chem. Theory Comput. 10, 2591-2598
  • Julija Zavadlav, Manuel N. Melo, Siewert J. Marrink, Matej Praprotnik, Adaptive resolution simulation of an atomistic protein in MARTINI water, J. Chem. Phys. 140, 054114

Teaching

Winter semester 2019/2020