Claudia Van Borkulo
Bestuursvoorzitter Stichting De Kleiacademie
Purmerend, North Holland, Netherlands
Summary
👤
Senior🎓
Top SchoolClaudia Van Borkulo is a methodological psychologist and research leader with 12 years of experience translating complex mental-health questions into rigorous, novel statistical approaches. She earned a cum laude PhD and an MSc in Psychological Methodology, and as a Postdoc at the University of Amsterdam and AMC developed a multi-timescale network modeling framework—work recognized with a VENI grant—within the interdisciplinary Urban Mental Health consortium. Her research blends theoretical rigor and applied inquiry into why individuals differ in susceptibility to urban-related mental health problems, and she has shifted focus from cross-sectional methods to intensive within-person measurement. Beyond academia she combines governance and teaching roles at De Kleiacademie and freelance work, demonstrating an ability to bridge research, education, and organizational leadership. Colleagues value her for turning abstract methodological challenges into usable tools and curricula that advance both science and practice. Based in Purmerend, she brings an uncommon mix of deep quantitative skill, interdisciplinary collaboration, and hands-on community engagement.
12 years of coding experience
7 years of employment as a software developer
Master of Science (MSc), Biochemistry and Molecular Biology, Master of Science (MSc), Biochemistry and Molecular Biology at Vrije Universiteit AmsterdamMaster of Science (MSc), Psychological Methodology (cum laude), Master of Science (MSc), Psychological Methodology (cum laude) at University of AmsterdamDoctor of Philosophy - PhD, PSYCHOLOGY, Cum laude, Doctor of Philosophy - PhD, PSYCHOLOGY, Cum laude at Rijksuniversiteit Groningen (University of Groningen)
Github Skills (1)
statistics8
Programming languages (1)
Github contributions (3)
cvborkulo/PercolationIndicator
Aug 2014 - Oct 2016
Contributions:2 commits, 1 push in 2 years 2 months
cvborkulo/IsingFit
Jan 2014 - Jun 2018
This network estimation procedure combines l1-regularized logistic regression with model selection based on the Extended Bayesian Information Criterion to identify relevant symptom-symptom relationships. These relationships define connections in a network.
Contributions:29 commits, 1 PR, 5 pushes in 4 years 5 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.