open PhD position in explainable and causal machine learning

Starting July 2024 (or later), and for a duration of 3 years (possibility to extend), Professor Markus Loecher at HWR Berlin is looking for a PhD candidate interested in the intersection of causal ML and explainable AI!

(pay grade 13 TV-L Berlin, with 66% of the regular weekly working hours)

Your tasks:
  • Advance current methods in causal ML such as double ML, honest trees, causal Shapley values, heterogeneous treatment effects, conditional feature attribution methods.
  • Research and improve the role of XAI methods in causal ML.
  • Seek cooperation with partners in the industry or research institutions.
  • Publish in international, peer-reviewed journals and on conferences.
  • Teaching load of 2.64 semester hours per week in the field of quantitative methods or statistics or economics or mathematics or business informatics.

Your profile:
  • A master's degree at a university or university of applied sciences in statistics, (business) informatics, economics or mathematics;
  • Demonstrated competencies in machine learning, data science or econometrics.
  • Strong background in data analysis, quantitative research and statistical reasoning.
  • High intrinsic motivation and independence, ability to work with others.
  • Excellent programming skills in R or python.
  • Very good communication and organisational skills (in English; German is desirable)

If interested, please contact me at

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