Electrochemist working where machine learning meets battery electrode manufacturing.
Industrial doctoral researcher (Dr.-Ing.) with VARTA Microbattery and TU Braunschweig, combining electrode
process development with process–property modelling. Earlier work spans cathode materials, electrochemical
characterisation, and laboratory automation. Particular interest in continual learning: how models absorb new
process regimes without discarding what they already know.
VARTA Microbattery GmbH · Ellwangen · with TU Braunschweig (iPAT)
Develop and qualify electrode processing routes — coating and calendering — for the CoinPower
lithium-ion button-cell range (9.4–16.1 mm diameter, 29–145 mAh).
Scaled a semi-dry electrode production route to 3 kg/h across several active-material chemistries.
Built a calendering-aware thermal-conductivity closure that cut prediction error across 27
calendering states from 31.1% to 4.5% MAPE, correcting the monotonic assumption behind porosity-only
models.
Strategy
Strategic Corporate Development
Jobvalley GmbH · Hamburg
Produced the market, competitor, and market-entry analyses behind the company's expansion into the
Netherlands, which launched as pilot projects.
Research assistant
Cathode Active Materials
Max Planck Institute for Solid State Research, with BASF · Stuttgart
Established viable precursor routes for NCA and NMC cathode active material, and showed that eutectic
lithium-source mixtures lower the calcination temperature of the lithiation step.
Team lead
Data Analyst, Team Lead
Eurofins Genomics · Munich
Led a 12-person data-analysis team for qPCR assay quality control, coordinating between laboratory
operations and customers.
Built out testing facilities and analysis workflows during the group's COVID-19 RT-PCR scale-up.
Research internships
MOF catalysis
Institute of Catalysis Research · Prof. Roland Fischer
Technical University of Munich
Synthesised porphyrin-based Zr-MOFs metalated with Ru, paired with imidazolium ionic liquids of
varying alkyl chain length, establishing a viable route to the catalyst pair.
Screened the pair for sequential catalysis — epoxidation followed by CO₂ fixation within a single
framework — in a programme transferring concepts from enzymatic catalysis to synthetic MOFs.
Laser spectroscopy
Chair of Physical Chemistry · Prof. Ulrich Heiz
Technical University of Munich
Commissioned a CD-REMPI setup, making two measurements possible on chiral species from laser
ablation: enantiomeric excess, and circular dichroism resolved through single vibronic transitions of
the intermediate electronic state.
Process development
Solid Oxide Fuel Cells
Robert Bosch GmbH · Bamberg
Scaled ceramic paste processing from laboratory batches to mass-production volumes, characterising
the rheology that governs coating quality.
Electrochemistry
Chair of Technical Electrochemistry · Prof. Hubert Gasteiger
Technical University of Munich
Helped develop an operando OEMS setup and ran the degradation quantification for the group's study of
proton intercalation in Ni-rich NCM, introduced by ashing and by improper handling or storage.
The measurements established a 200 mV first-charge diffusion overpotential at only 2 mol%
intercalated protons, even at C/50, and tracked the electrochemical deintercalation of those protons
above 4.5 V vs Li.
Education
Doctorate
Dr.-Ing. Candidate, Mechanical Engineering
TU Braunschweig · Institute for Particle Technology (iPAT), Particle Simulation
& Functional Structures
Supervisor: Prof. Dr.-Ing. Carsten Schilde. Industrial doctorate in cooperation with VARTA
Microbattery GmbH.
Machine learning for lithium-ion electrode manufacturing: process–property modelling of calendered
electrodes, and continual learning under process drift.
Derived a replay-free, Fisher-free continual-learning controller (IGFA) that reduces forgetting by
36% against naive continual fine-tuning of a 410M-parameter language model while improving adaptation
(p ≤ 0.024, three seeds), carrying only a low-rank subspace as state.
Continuing education
Machine Learning
Technical University of Munich · enrolled student
Graduate coursework in Machine Learning and Data Science, alongside independent projects, undertaken
before beginning doctoral research.
Google × Kaggle 5-Day AI Agents Intensive.
M.Sc.
M.Sc. Chemistry
Technical University of Munich · focus: electrochemistry and materials science
Thesis: built an automated scanning droplet cell with accompanying data models, enabling systematic
high-throughput electrochemical screening of Prussian blue analogues.
B.Sc.
B.Sc. Chemistry and Biochemistry
Ludwig Maximilian University of Munich · final grade 1.3 (German scale, 1.0 best)
Thesis: screened a series of lithium sources and quantified how each shapes the calcination of NCA
cathodes.
Störk, J. Interference and retention in continual learning — forgetting as weight-interference
energy, and a replay-free structural controller (IGFA). arXiv:2607.09202
Störk, J. Capturing the calendering U-shape in lithium-ion electrode thermal conductivity — a
calendering-aware Zehner–Bauer–Schlünder closure. arXiv:2607.11521
Skills
Analytical
XRD, SEM, TGA, XPS, FTIR, GC/MS; impedance spectroscopy, galvanostatic cycling, and online electrochemical
mass spectrometry (OEMS).
Computational
Python (pandas, NumPy, SciPy), MATLAB, SQL; machine learning, with emphasis on continual-learning
methods.
Engineering
CAD (SolidWorks, AutoCAD); laboratory automation and instrument control.