Eric continues Jakob's work on large-scale tissue simulations using cellular Potts models. His current focus lies in understanding emergent properties during tumor growth. As a member of the NIC research group "Computational Structural Biology", his regular workplace is at Forschungszentrum Jülich.
Christian works on contact prediction of RNA, using methods of statistical physics like direct coupling analysis. This method is an example of an inverse statistical mechanics model and highly related to the inverse Ising model. As a member of the NIC research group "Computational Structural Biology", his regular workplace is at Forschungszentrum Jülich.
Fathia works in the field of computational chemistry. As a member of the DFG research training group 2450 - "Tailored Scale-Bridging Approaches to Computational Nanoscience", she develops a multi-scale computational framework to simulate enzymatic processes and related large-scale conformational transitions using the example of sensor histidine kinases.
Julian's interest lies in combining data science with biophysical simulations. He tries to find ways to incorporate machine learning techniques to improve the quality of cell-resolved tissue simulations as used in Jakob's work. Julian is a member of the Helmholtz Information & Data Science School for Health (HIDSS4Health).
Oskar works on novel memory-intensive machine learning techniques for protein phenotype prediction.
Arthur works on protein structure prediction by integrating co-evolutionary data into explicit-solvent molecular dynamics simulations.
Jakob works on simulations of cell-resolved tissue dynamics. Using the cellular Potts model, he tries to describe pattern formations and conformation changes in tissue in cases like embryogenesis and tumor growth. As a member of the NIC research group "Computational Structural Biology", his regular workplace is at Forschungszentrum Jülich.
Marie works on the integration of the limited information from small-angle X-ray scattering into molecular dynamics simulations using structure-based models. Using computational-intelligence based methods such as particle swarm optimization, she tries to improve the performance of biomolecular simulation protocols.
We have always openings for Bachelor and Master students. Do not hesitate to contact us if you are interested!
- Dr. Emanuel Peter 2020
- Dr. Fabrizio Pucci 2020
- Dr. Ines Reinartz 2014 - 2019
- Dr. Ilaria Mereu 2014 - 2015
- Dr. Shalini John Lovis 2014 - 2015
- Dr. Abhinav Verma 2011 - 2013 (now Shell India)
- Dr. Marie Weiel-Potyagaylo (2021), Deriving Protein Structures Efficiently by Integrating Experimental Data into Biomolecular Simulations
- Dr. Jakob Rosenbauer (2021), Multiscale Modeling of Tumor Development
- Dr. Mehari Zerihun (2021), RNA Structure Prediction Guided by Co-Evolutionary Information – Method Development and Applications
- Dr. Momin Ahmad (2020), High-Throughput screening of the CoRE MOF database to predict cross-linking of Metal-Organic Frameworks
- Dr. Ines Reinartz (2019), Simulation and Analysis of Protein-Fluorophore Systems for Comparison with Fluorescence Spectroscopy Data
- Dr. Claude Sinner (2017), Computational Insights into Zebrafish Brain Development during Gastrulation
- Dr. Benjamin Lutz (2014), Multiscale Simulation and Analysis of Structured Ribonucleic Acids
- Arthur Voronin (2018, now PhD student at KIT)
- Oskar Taubert (2018, now PhD student at KIT)
- Marie Weiel-Potyagaylo (2017, now PostDoc at KIT)
- Jakob Rosenbauer (2017, now PostDoc at FZJ)
- Ines Reinartz (now PostDoc at KIT)
- Lars Franke (2018)
- Linda Neubrand (2017)
- Fabian Nagel (2015)
- Sebastian Ratz (2015)
- Ramneek Singh (finishing his studies at Indian Institute of Technology (IIT), Kharagpur, India)
- Harsh Bajaj (finishing his studies at Indian Institute of Technology (IIT), Kharagpur, India)