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Research Scientist at Google Deepmind
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Vision - Machine Learning - Deep Learning
Université Grenoble Alpes
Doctor of Philosophy (PhD), Computer Science
January 1, 2009 – January 1, 2012
University of Amsterdam
Master, Artificial Intelligence
January 1, 2001 – January 1, 2007
College de Klop
VWO (dutch A levels)
January 1, 1994 – January 1, 2000
Google DeepMind
Senior Research Scientist
May 1, 2024 – Present
Senior Research Scientist
March 1, 2019 – May 1, 2024
Amsterdam Area, Netherlands
University of Amsterdam
Guest Researcher Computer Vision Group
March 1, 2019 – December 1, 2021
Amsterdam Area, Netherlands
University of Amsterdam
Assistant Professor 3D Deep Learning
February 1, 2017 – February 1, 2019
Amsterdam Area, Netherlands
UC Berkeley Electrical Engineering & Computer Sciences (EECS)
Visiting Researcher
January 1, 2016 – March 1, 2016
San Francisco Bay Area
University of Amsterdam
PostDoc in Computer Vision and Machine Learning
November 1, 2012 – January 1, 2017
Amsterdam Area, Netherlands
NICTA
Visiting Researcher
March 1, 2011 – June 1, 2011
Canberra, Australia
Xerox Research Centre Europe
PhD Student
October 1, 2009 – October 1, 2012
INRIA Rhone Alpes
PhD Student
February 1, 2009 – November 1, 2012
Radboud University Nijmegen
Research Intern
May 1, 2008 – October 1, 2008
INRIA
Research Intern
September 1, 2007 – March 1, 2008
LEAR INRIA-Rhone Alpes
IBM
Extreme Blue Summer Internship
June 1, 2005 – August 1, 2005
Cultural Fit Analysis
The candidate's background is heavily skewed towards advanced research and academia in Computer Science and AI, with a strong focus on Computer Vision and Machine Learning. While these skills are highly technical, the target role is 'Data Analyst'. This represents a significant mismatch in the typical day-to-day responsibilities and focus. A Data Analyst role usually requires strong business acumen, data visualization, SQL, and practical application of statistical methods to business problems, which are not explicitly highlighted in the candidate's research-heavy profile. The candidate's experience is more aligned with a Data Scientist or Machine Learning Engineer role.
Soft Skills & Operational Fit
The candidate's extensive research and academic background suggests strong analytical thinking, problem-solving, and independent work skills. Experience in various research groups and universities implies adaptability and collaboration within scientific environments. However, the provided data does not offer specific insights into communication style, stress handling, or team collaboration in a corporate data analyst setting.