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Machine Learning
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Quantitative researcher at G-Research. Previously a Senior Researcher at Microsoft Research. Earlier in my career I interned with teams at Google Health, Facebook AI Research, and Google X. I hold a PhD in machine learning from Imperial College London.
Imperial College London
Doctor of Philosophy (PhD), Probabilistic and Causal Reasoning in Deep Learning for Imaging
January 1, 2016 – January 1, 2021
The University of Edinburgh
Master of Science (MSc), Artificial Intelligence
January 1, 2015 – January 1, 2016
University of Leeds
Bachelor of Science (BS), Physics
January 1, 2013 – January 1, 2014
Humboldt-Universität zu Berlin
Bachelor of Science (BS), Physics
January 1, 2011 – January 1, 2014
Landesgymnasium Sankt Afra, Meißen, Hochbegabtenförderung
Abitur, Examination subjects: Maths, Physics, German, History and a coursework in Physics
January 1, 2005 – January 1, 2011
G-Research
Quantitative Researcher
September 1, 2024 – Present
Greater London, England, United Kingdom · On-site
Microsoft
Senior Researcher
November 1, 2021 – July 1, 2024
Cambridge, England, United Kingdom
Student Researcher
December 1, 2020 – September 1, 2021
Research Intern
June 1, 2020 – December 1, 2020
PRO Unlimited @ Facebook
Research Collaborator
March 1, 2019 – June 1, 2019
London, Greater London, United Kingdom
Research Intern
September 1, 2018 – December 1, 2018
Montreal, Canada Area
X, the moonshot factory
Machine Learning Resident
May 1, 2018 – August 1, 2018
San Francisco Bay Area
Rasa
Machine Learning Engineer
March 1, 2017 – May 1, 2018
Broad Institute
Visiting Scholar
May 1, 2016 – August 1, 2016
Greater Boston Area
Fraunhofer-Institut für Physikalische Messtechnik IPM
Intern
April 1, 2015 – August 1, 2015
Freiburg Area, Germany
Robert Bosch Power Tools
Intern
September 1, 2014 – March 1, 2015
Penang, Malaysia
Bildung & Begabung
Course Instructor at Talentakademie Ruhr 2014
July 1, 2014 – July 1, 2014
Westfälische Hochschule
Fraunhofer FOKUS
Student Research Assistant
January 1, 2012 – August 1, 2013
Berlin Area, Germany
Cultural Fit Analysis
The candidate's career trajectory is heavily skewed towards research and academia, with roles at prominent research institutions and tech giants' research divisions. While this demonstrates intellectual rigor, the alignment with a pure 'Backend Engineer' role, which typically involves more product development, system architecture, and operational responsibilities, is not explicitly clear from the provided experience descriptions. The diversity of projects and roles, from physics to AI and early software development, suggests adaptability. However, the lack of detailed project descriptions makes it difficult to assess the depth of collaboration and product-focused contributions.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong problem-solving, critical thinking, and independent learning abilities. The experience as a course instructor indicates communication and mentoring skills. However, the provided data does not offer direct insights into stress handling, team collaboration, or work attitude beyond the psychometric test's evaluation focus.