I'm an applied mathematician and completed my postdoc stages as detailed below.
I'm currently aspiring to transit from pure academia to R&D industry by the end of 2026.
An excerpt of my works are showcased below. I'm mainly interested in applying novel and established mathematical tools in the field of systems biology for conducting pre-clinical and translational research in the life sciences.
If my background and skills match your company's profile, I would be happy to connect - please reach out via the contact information below.
Up to mid of 2026, I am/was a postdoctoral fellow in the lab of Jan Hasenauer where my research revolves around the interfaces of life sciences, mathematics and computer science. We developed mechanistic models (ODE/PDEs) and applied methods of parameter estimation in Julia/Python to calibrate models and to shed light on the interplay / ramifications of dynamical biological processes in cells in the special research fields BATenergy and Metaflammation. Therefore we leveraged AI-tools, artificial neural networks/deep learning approaches and recent advances in bioinformatics on high-performance computing infrastructure. We developed pipelines for statistical data analysis and visualization (R/Python, Javascript/Typescript) of large-scale data sets, knowledge representation and reasoning on metadata using semantic web technologies (graph databases, SPARQL, ontologies in OWL format) focusing on reusability, repeatability and reproducibility.
I've actively maintained / contributed to the following repositories:
- https://github.com/ICB-DCM/pyABC - a framework for distributed, likelihood-free inference
- https://github.com/stephanmg/calorimetry - a Shiny/R application for analysis of indirect calorimetry datasets
- https://github.com/ICB-DCM/pyPESTO - a python Parameter EStimation TOolbox
- https://github.com/stephanmg/Shiny-PWAS - a Shiny/Python application to access the ExPheWas database
Up to 2020 I have been working in the field of computational neuroscience under supervision of the Queisser lab. I developed novel numerical methods and grid generation tools for modelling and simulation of spatially-resolved intracellular ion dynamics in neurons by PDEs/ODEs on HPC/HTC infrastructure. We made use of GPU programming on NVIDIA GPUs through CUDA/cg shader programming for interactively visualizing and numerical analysis of scientific data sets in the virtual reality framework Unity VR (C#). Major programming experience stems from C++/C and Lua, Java and Python. I developed prior to that also numerical models for multi-scale and hybrid-dimensional phenomena in molecular dynamics/computational neuroscience and mesh generation methods for the study of intracellular Calcium waves, neuronal plasticity and memory formation.
I have been a contributor to the following repositories:
- https://github.com/c2m2/Neuro-VISOR/ - Virtual Interactive Simulation Of Reality for simulation of neuronal dynamics
- https://github.com/ug4 - UG4 simulation framework. Solving differential equations on unstructured finite element grids.
- https://github.com/NeuroBox3D - A visual toolbox for simulation of neuronal activity in hybrid 1D/3D settings
- https://github.com/stephanmg/VRL-SWC-Density-Vis - A Java application for density analysis of stacks of neuronal morphologies (NeuroMorpho.org)
You can find my works on ResearchGate.
Contact information can be found on the left most panel - feel free to browse my recent and public projects.
For secure e-mailing find my GPG fingerprint as: F598 BCFF 445C C90F 3312 3C71 7D30 C7E5 7559 76A6.