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IBPT 02-2022 Master thesis: Multiobjective Bayesian optimization of the KARA injection process


Institut für Beschleunigerphysik und Technologie (IBPT)


A reliable, reproducible, and stable beam injection process with a simple set-up and operation can considerably shorten the turnaround time, i.e. the time between beam dump and stable top-energy beams, which can be used by the experimental beamlines. Ideally, it would also allow to inject the maximum number of particles with a low fraction of beam loss and with a minimum perturbation to any circulating beam. At KIT the first steps in automating the injection process have been taken, applying Bayesian optimization with promising results. This project will focus on extending the algorithm to a multiobjective Bayesian optimization one. A multiobjective Bayesian optimization algorithm would allow to simultaneously trade-off between multiple objectives and find optimal settings for user-specific cases, which is of particular interest during special runs. More precisely, the algorithm will include the beam orbit as a new objective. The beam orbit is distorted by the algorithm creating unnecessary trajectory deviations, which could lead to beam losses at higher currents. This project can continue into a doctoral thesis.


as soon as possible

Persönliche Qualifikation

  • Student in Physics
  • Fluency in English
  • Basic programming skills in Python and willingness to learn
  • Interest in research and in experimental work
  • Ability to work reponsibly and independently

Contract duration

according to the study regulation

Contact person in line-management

For further information, please contact Dr. Andrea Garcia, phone +49 721 608-26117, email: or Chenran Xu, phone + 49 721 608-23353, email:

Bitte bewerben Sie sich online über den unten stehenden Button für die Ausschreibungsnummer IBPT 02-2022.

Ausschreibungsnummer: IBPT 02-2022

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