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Architect AI Measurement Systems | Tools and Machine Learning For Biotech
I design measurement systems that don't exist yet - combining academic literature analysis with custom AI architectures to enable breakthrough products in biotech. My approach: Literature analysis → identify what's theoretically possible but not implemented Custom AI architecture → novel solutions tailored to your measurement challenges Protocol optimization → extract maximum information for AI applications System integration → from concept to working breakthrough Recent results: - Reduced experimental requirements by 10-1000x through intelligent design - Built state-of-art architectures solving "impossible" sparse-data problems - Optimized Raman spectroscopy protocols for AI-powered diagnostics - Custom 5x RTX 3090 development rig + terminal-only workflow for maximum performance If your team has measurement challenges that standard solutions can't solve, let's discuss how custom AI architecture might unlock your breakthrough.
University of Groningen
Doctor of Philosophy - PhD, Theoretical and Mathematical Physics
September 1, 2010 – September 1, 2014
University of Cambridge
Master of Advanced Studies in Mathematics, Mathematics and Theoretical Physics
January 1, 2009 – January 1, 2010
Universidad Autónoma de Madrid
Exchange student, Master High Engery Physics
January 1, 2007 – January 1, 2007
University of Groningen
Master in Physics, Theoretical Physics
January 1, 2006 – January 1, 2009
University of Groningen
Bachlor in Phyiscs, Physics
January 1, 2003 – January 1, 2006
Data Driven Lab Consulting
Machine learning scientist
May 1, 2024 – Present
Amsterdam-Zuid, North Holland, Netherlands · Hybrid
Huawei
Machine learning expert and team lead
July 1, 2020 – April 1, 2023
Amsterdam · Hybrid
Go Grow AI
Lead Data Scientist
May 1, 2020 – Present
Amsterdam, North Holland, Netherlands · On-site
Antler
Entrepreneur In Residence
January 1, 2020 – April 1, 2020
Amsterdam
TomTom
Senior Software Engineer
August 1, 2018 – January 1, 2020
NHL Stenden
Lecturer Machine learning
February 1, 2018 – July 1, 2018
Leeuwarden Area, Netherlands
ING
Machine learning developer
December 1, 2015 – February 1, 2018
Amsterdam
Independent View
Quantitative researcher
December 1, 2014 – December 1, 2015
Amsterdam
Data consultancy
Machine Learning Engineer
August 1, 2014 – November 1, 2014
Tokyo
FOM
PhD in theoretical physics
September 1, 2010 – September 1, 2014
Groningen Area, Netherlands
Rijksuniversiteit Groningen
Teaching Assistant
March 1, 2006 – August 1, 2009
Groningen, Netherlands
Biblionet Groningen
Web developer
October 1, 2002 – October 1, 2003
Groningen, Netherlands
Hanzehogeschool Groningen / Hanze University of Applied Sciences Groningen
System administrator
March 1, 2000 – November 1, 2001
Groningen, Netherlands
Shandong Linyi-Cambridge Maths Summer School
August 1, 2010 – Present
With ten master students from Cambridge University we organized a summer school for bachelor students in mathematics. I taught a course on group theory.
Getting and Cleaning Data
Coursera
June 24, 2026 – Present
The Data Scientist’s Toolbox
Coursera
June 24, 2026 – Present
Exploratory Data Analysis
Coursera
June 24, 2026 – Present
Machine Learning
Coursera
June 24, 2026 – Present
Statistical Inference
Coursera
June 24, 2026 – Present
Reproducible Research
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate has a diverse background spanning academia, large corporations (Huawei, TomTom, ING), startups (Antler, Go Grow AI), and freelance consulting. This breadth of experience suggests adaptability to various organizational cultures. The role as 'Data Analyst' is a slight shift from their predominant 'Machine Learning Scientist/Engineer' and 'Lead Data Scientist' roles, which are typically more focused on model development and deployment rather than pure analysis. While the analytical skills are undoubtedly present, the direct alignment with a 'Data Analyst' role, which often emphasizes SQL, dashboarding, and business intelligence, is not explicitly demonstrated through specific tools or projects in the resume. Their experience is heavily skewed towards advanced ML/AI development. The project diversity is high in terms of technical domains but less so in terms of typical data analyst responsibilities.
Soft Skills & Operational Fit
The candidate's extensive experience in leading teams, mentoring, and teaching suggests strong leadership, communication, and collaboration skills. Their entrepreneurial roles and diverse project experience indicate adaptability and a proactive approach. The academic background in theoretical physics points to a strong foundation in complex problem-solving and analytical thinking, which are crucial for a senior data analyst role. However, the provided data does not include specific soft skill assessments (e.g., psychometric test results are 0), so a definitive operational fit assessment is limited to inferences from their professional history.