Benjamin Schwenker is a PostDoc and data scientist with nine years of experience at Georg-August-Universität Göttingen and long-standing membership in the international Belle II collaboration, where he contributed to the design, simulation and commissioning of a pixel vertex detector installed in 2023. He combines deep expertise in statistical data analysis, Python and C++ development with practical experience in Kalman-filter based tracking, detector alignment and fast detector simulation for large-scale HEP software frameworks. Benjamin has taught statistical methods, supervised thesis work at multiple levels, and held coordination roles that honed his leadership in international, agile teams. He translated research into practical tools—most notably a localized material-budget measurement method that was adopted beyond Belle II for ATLAS ITk prototypes at CERN—demonstrating an ability to move techniques from prototyping to wider experimental use. Now seeking application-oriented projects, he aims to apply his cross-disciplinary skills in statistics, ML and quantitative analysis to problems with direct practical relevance.
9 years of coding experience
Promotion, Physics, magna cum laude, Promotion, Physics, magna cum laude at Georg-August-Universität Göttingen
Vordiplom, Physics, sehr gut, Vordiplom, Physics, sehr gut at Universität Rostock
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