Knut Zoch, Ph.D.

Postdoctoral Fellow in Experimental Particle Physics at Harvard University

Teaching & Mentoring

I’m passionate about making complex ideas accessible — whether through university courses, research supervision, or interdisciplinary workshops. My goal is to help students develop practical skills, gain confidence in applying them, and grow as independent researchers.

University Teaching

Over the past years, I’ve contributed to teaching at both undergraduate and graduate levels, often helping develop first-time course offerings in data analysis and machine learning. My teaching focuses on problem-solving, hands-on exercises, and applying tools to real research challenges.

Selected courses:

  • Statistical Methods in Physics — Univ. of Geneva (Fall 2021, Fall 2022) ★
  • Top Quark Physics — Univ. of Göttingen (Winter 2020/21)
  • Advanced Statistical Methods in Data Analysis: Machine Learning — Univ. of Göttingen (Summer 2019) ★
  • Intro to Nuclear & Particle Physics — Univ. of Göttingen (2016–2019)

★ Indicates courses where I played a central role in developing new content and structure — including tutorial materials, hands-on exercises, final projects, and assessment tools — particularly for courses being offered for the first time.

Earlier in my academic career, I also supported a range of introductory lab and lecture courses, including Experimental Physics I (Mechanics & Thermodynamics) and Essentials of Experimentation.

Mentoring and Supervision

I’ve supervised student research at all levels, including undergraduate interns, master’s students, and Ph.D. candidates — across institutions like Harvard, Geneva, and Göttingen.

Project topics include:

  • Top-quark measurements and rare production modes
  • Machine learning for reconstruction and regression
  • Searches for long-lived particles and anomalies

Many of these collaborations led to peer-reviewed publications or conference presentations. I support students closely, especially in the early stages, while encouraging ownership of their projects. Several examples are described on the research page.

Interdisciplinary Workshops

Since 2019, I’ve co-led machine learning workshops at international summer schools organized by the German Academic Scholarship Foundation. These programs bring together students from a wide range of disciplines — from physics to political science — for an in-depth look at data-driven methods and their societal impact.

Recent workshops:

  • 2025: Banz Castle, Germany (planned)
  • 2024: Ljubljana, Slovenia
  • 2021: Koppelsberg, Germany
  • 2019: St. John’s College, Cambridge, UK

Workshops combine interactive lectures, coding exercises, team projects, and open discussions — covering topics like supervised learning, generative models, and algorithmic fairness.

Invited Lectures and Training

I also contribute to training events for research collaborations and early-career scientists.

  • ERUM Data Hub Deep Learning School (2025, Aachen) Transformers and Prompt Engineering — Lecture and live coding session on ML applications in science

  • ATLAS Newcomers Lecture Series (2023, CERN) Top Quark Physics in ATLAS — Introductory lecture for new collaborators

If you’re interested in research supervision, teaching collaborations, or bringing particle physics or machine learning into your course or event, feel free to get in touch.