Summary
Maximilian Mordig is a doctoral researcher in machine learning at the Max Planck Institute and ETH Zürich with a decade of hands-on experience bridging deep learning, NLP, and applied analytics across tech, finance, and bioinformatics. His background combines top-tier academic training in physics and computational science (EPFL, Imperial College, Universidad de Granada) with industry work at Roche, where he built reproducible CI/CD and containerized pipelines for clinical-trial biometrics and interactive R tools. He brings strong analytical rigor from physics to tackle noisy biological and clinical data, having also improved genomic variant alignment and image-processing tooling during industry internships. Fast to learn and comfortable moving ideas into production, he is actively seeking PhD internships that connect foundational ML research with real-world deployments.
10 years of coding experience
Bachelor's degree, Physics, > 80%, Bachelor's degree, Physics, > 80% at Imperial College London
Master's degree, Computational Science & Engineering, 5.38 / 6, Master's degree, Computational Science & Engineering, 5.38 / 6 at Ecole polytechnique fédérale de Lausanne
Master's degree, Physics and Mathematics, Master's degree, Physics and Mathematics at Universidad de Granada
German, English, French, Spanish, Chinese