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Senior Scientist bei Philips
Ulf studied Scientific Computer Science at Bielefeld University/Faculty of Technology with a major focus on machine learning and data mining. After receiving his diploma (German eq. to M.Sc.) in 2005, he worked as a software developer. Between 2009 and 2013, he was at the CITEC graduate school and member of the CITEC research groups Ambient Intelligence and Sociable Agents. Afterwards, Ulf worked as a postdoctoral researcher at Eindhoven University of Technology and was member of the Activity and Context recognition Technologies research group (ACTLab) and the GreenerBuildings project funded under the European Seventh Framework Programme (FP7). In this context, he was working on an activity-aware framework for saving energy and enhancing occupant comfort in commercial buildings. Currently, Ulf works as a Data Scientist at Holst Centre for imec Netherlands. Ulf has a strong background in data mining and machine learning algorithms.
Bielefeld University
Diplom (eq. Master's degree), Scientific Computer Science
January 1, 2005 – Present
Center for Cognitive Interaction Technology
PhD
N/A – Present
Philips
Senior Scientist
April 1, 2019 – Present
Eindhoven und Umgebung, Niederlande
Philips
Scientist - Deep Learning
June 1, 2016 – Present
Eindhoven und Umgebung, Niederlande
imec
Researcher - Data Scientist on Body Area Networks
September 1, 2014 – June 1, 2016
Eindhoven und Umgebung, Niederlande
Philips
Visiting Researcher
December 1, 2013 – August 1, 2014
Eindhoven und Umgebung, Niederlande
Eindhoven University of Technology
Post Doctoral Researcher
March 1, 2013 – August 1, 2014
Eindhoven
CITEC Cognitive Interaction Technology - Center of Excellence
Ph.D. scholarship holder
January 1, 2008 – March 1, 2013
Bielefeld
HKS Systeme GmbH
Software developer
January 1, 2006 – January 1, 2007
Parderborn
Cultural Fit Analysis
The candidate's background is heavily weighted towards academic research and scientific roles. While this demonstrates deep technical expertise, the transition to a corporate Data Analyst role might require adaptation to different operational rhythms, project delivery methodologies, and stakeholder management. The diversity of projects is not explicitly detailed, making a full assessment of cultural fit challenging without more information on their practical application of skills outside of research.
Soft Skills & Operational Fit
The candidate's extensive research background suggests strong analytical thinking, problem-solving, and independent work capabilities. However, specific soft skills like teamwork, communication, and adaptability in a corporate data analyst setting are not explicitly detailed in the provided data. The psychometric test results are not available to assess these aspects.