Fellow Detail

Photo of Pablo Bernabeu
Name Pablo Bernabeu
Affiliation
Research area code (C8) Psychology
Fellowship Inauguration Year 2020
Website https://pablobernabeu.github.io
RSS/Atom Feed https://pablobernabeu.github.io/categories/r/index.xml
ORCID 0000-0003-1083-2460
Google Scholar https://scholar.google.co.uk/citations?user=DxD0QDoAAAAJ
GitHub pablobernabeu
LinkedIn pablobernabeu
Interests

Software: R, online data dashboards, virtual environments. Science: cognitive psychology and neuroscience, psycholinguistics, open data, reproducibility.

Short Biography

I am a data analysis specialist with nearly a decade of experience in academic and industry. My skill set includes research, statistics, technical documentation, R, HTML, Javascript, SQL, Unix and high-performance computing.

I developed my analytical skills during my Research Master’s program in Language and Communication at the universities of Tilburg and Radboud, where I conducted an electroencephalography study and pursued advanced courses in statistical modeling and programming. This foundation was further expanded during my PhD at Lancaster University, where I investigated the comprehension of meaning in language, employing multilevel statistical models and developing innovative methodologies for experimental data analysis.

In my postdoctoral fellowship at UiT The Arctic University of Norway, I continued using R, Javascript and Unix to create experimental studies and analyse the results. I also provided statistical consultancy for research projects, offering expertise in data preprocessing, analysis and visualization. Alongside my academic endeavours, I contributed to the technology sector as a Service Analyst at Onfido, where I utilized data science and business analytics to monitor and enhance semi-automatic identity verifications.

With a robust portfolio of research, programming and statistics, I bring a unique combination of academic and industry experience, positioning myself as a versatile and innovative data analyst adept at solving complex problems across diverse domains.

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