Curriculum vitae

• Feb 2024 – present

  Postdoctoral Data Scientist, AI for Oncology & Precision Medicine

  LMU University Hospital (LMU Klinikum), Munich

  Built an end-to-end pipeline predicting more than 80 molecular targets from H&E whole-slide images (AUROC up to 0.90 on external validation, three cohorts). Developed a Cox-regression tool that supports treatment planning for brain metastases. Led part of an LMU and Helmholtz Munich project benchmarking published predictive indices against evolutionary-algorithm models. Derived patient subtypes with unsupervised ML and linked them to outcomes. Delivered containerized, reproducible ML on HPC and worked daily with clinicians and national consortia (DKTK, BZKF).

• Sep 2020 – Dec 2023

  Data Scientist (PhD Researcher), Computational Biology & Data Science

  Technical University of Munich (TUM), Freising

  Designed, implemented, and benchmarked two open-source tools for genome-scale methylation analysis (jDMRgrid, DMRspiker), from algorithm to public release. Built CNN and LSTM models in TensorFlow over large-scale unstructured genomic data. Integrated multi-source omics into statistical models linking molecular variation to phenotype, which led to co-first authorship.

• Feb 2017 – Aug 2020

  Data Scientist, Research Student in Data Science & Bioinformatics

  Silesian University of Technology, Gliwice

  Ran machine-learning radiomics on medical imaging to predict clinical outcomes and built biostatistical analyses of proteomics and genomics data. Built an automated computer-vision system to detect liver metastases in MRI (MSc thesis).

• 2018 – 2019

  Software Engineer (Intern / Contractor)

  WASKO S.A. / Gabos Software, Gliwice

  Developed SQL reporting for MEDICUS, a hospital CRM application supporting operational healthcare workflows.

• 2020 – 2026

  Dr. rer. nat. (PhD) in Bioinformatics (epigenomics and machine learning)

  Technical University of Munich

  Thesis submitted April 2026; defense expected autumn 2026.

• 2019 – 2020

  MSc, Data Science

  Silesian University of Technology

  Graduated with distinction. Final grade 5.0, GPA 4.86/5.0.

• 2015 – 2019

  BEng, Bioinformatics

  Silesian University of Technology

  Final grade 5.0/5.0; GPA 4.76/5.0.

Core

Python · R · SQL · scikit-learn · PyTorch · TensorFlow · pandas · NumPy

Tools & cloud

AWS · Azure · Docker · Apptainer/Singularity · Git · Linux/HPC · Tableau · Plotly · R Shiny

Methods

Predictive modeling · survival analysis · deep learning (CNN/LSTM, attention/MIL, foundation models) · unsupervised clustering · model validation & benchmarking · reproducible ML / MLOps · LLM & agentic workflows

Domains

Healthcare & life sciences · oncology & precision medicine · clinical decision support · imaging, omics & clinical data

• Co-first-authored, peer-reviewed publication (see Publications)
• [FILL IN: talks, posters, peer review, awards, or fellowships]

Polish (native) · English (C2, full professional) · German (B2, working proficiency)