Benjamin Jurke is Head of Machine Learning at Beckhoff Automation with a decade of experience turning mathematical physics and advanced ML into production-ready, real-time industrial automation systems. He leads development of the TwinCAT Machine Learning and Neural Network runtime that embeds ML directly into control loops—technology that powers the XPlanar motion controller and earned an internal innovation award. Trained as a PhD mathematical physicist with postdocs and an Executive MBA, he bridges deep theoretical rigor with product-focused engineering and business insight. His background includes leading research at DMG MORI on IIoT and adaptive CNC systems and teaching big data analytics, reflecting a rare mix of academic depth, applied R&D, and industrial deployment experience. Notably, he pairs formal scientific training with hands-on nanodegrees in reinforcement learning and robotics to drive real-time AI in automation.
10 years of coding experience
6 years of employment as a software developer
Executive MBA Business Administration and Management General, Executive MBA Business Administration and Management General at University of Münster
Diplom-Mathematiker (= M.Sc.) Math, Diplom-Mathematiker (= M.Sc.) Math at Bielefeld University
Dr. rer. nat (= PhD) Mathematical Physics, Dr. rer. nat (= PhD) Mathematical Physics at Ludwig-Maximilians-Universität München
Nanodegree Deep Reinforcement Learning, Nanodegree Deep Reinforcement Learning at Udacity
Abitur, Abitur at Ratsgymnasium Wiedenbrück
PostDoc Theoretical and Mathematical Physics, PostDoc Theoretical and Mathematical Physics at Northeastern University
PostDoc Theoretical and Mathematical Physics, PostDoc Theoretical and Mathematical Physics at Max Planck Institute for Physics
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Benjamin Jurke - Head Of Machine Learning at Beckhoff Automation