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ML Research @ Merantix Momentum | PhD from University of Amsterdam
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
University of Amsterdam
Doctor of Philosophy - PhD, Machine Learning
March 1, 2023 – Present
University of Tübingen
Master of Science, Neural Information Processing
January 1, 2011 – January 1, 2013
Linköping University
Semester Abroad, Cognitive Science
January 1, 2009 – January 1, 2010
University of Osnabrück
Bachelor of Science, Cognitive Science
January 1, 2007 – January 1, 2011
Soofi
Project Member
September 1, 2025 – Present
Merantix Momentum
Senior Machine Learning Researcher
March 1, 2024 – Present
Berlin, Germany
MIDAS.lab @ Max-Planck-Institute for Intelligent Systems
Research Scientist - Machine Learning
July 1, 2020 – June 1, 2023
Tübingen, Baden-Württemberg, Germany
University of Amsterdam
Research Scientist - Machine Learning
January 1, 2015 – January 1, 2020
Max Planck Institute for Biological Cybernetics
Research Assistant - Machine Learning
November 1, 2013 – August 1, 2014
Tübingen, Germany
Neural Information Processing Group, University Tübingen
Research Assistant - Psychophysics
January 1, 2013 – July 1, 2013
Tübingen, Germany
Bernstein Center for Computational Neuroscience Tübingen
Teaching Assistant - Machine Learning
October 1, 2012 – January 1, 2013
Graduate Training Centre of Neuroscience, Tübingen University, Tübingen, Germany
Max Planck Institute for Biological Cybernetics
Research Assistant - Psychophysics
October 1, 2011 – March 1, 2012
Tübingen, Germany
Cultural Fit Analysis
The candidate's background is heavily academic and research-oriented, which aligns well with roles requiring deep technical expertise and innovation. The diversity of institutions (University of Amsterdam, Max-Planck-Institute, University of Tübingen) indicates adaptability to different research environments. The current role at Merantix Momentum and involvement with Soofi suggest a transition towards more applied or industry-relevant ML, which could indicate a good cultural fit for an ML Engineer role in a forward-thinking organization.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong analytical thinking, problem-solving, and independent work capabilities. However, specific data on collaboration, communication, and project management in a fast-paced industry setting is not explicitly provided.