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kai-lim/README.md

Hi there 👋

I am a data scientist at Roche.

Prior to this I did my PhD in statistical genetics at King's College London, analysing huge epidemiological datasets using genomic data science/causal inference methods, focusing on self-harm and its risk factors.

My passion lies in health data science and statistical genetics.

I use R, git, Linux/Unix, High Performance Computing (HPC), and am familiar with Python and SQL.

View my LinkedIn profile here and my Google Scholar profile here.

My recent projects

  1. Health Data Science Resources

I curate a list of resources related to health data science

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  1. ADHD_birthweight ADHD_birthweight Public

    My first published paper and R project. In this study I used co-twin design and latent growth modelling to investigate if birth weight is on the causal pathway to ADHD development.

    HTML

  2. UKB_selfharm UKB_selfharm Public

    This is one of my PhD data science projects. I used UK Biobank, a huge dataset with ~250K individuals in my research to study the aetiology of self-harm using genetic causal inference methods.

    HTML 3

  3. twin_modelling twin_modelling Public

    This is one of my PhD projects, where I employed twin modelling, a structural equation modelling approach to study the aetiology of self-harm and its genetic and environmental relationship with oth…

    HTML 3

  4. LondonGeneticsNetwork LondonGeneticsNetwork Public

    I use this repo to create a website for London Genetics Network and deploy it through Netlify.

    CSS 2 3

  5. sdghackathon sdghackathon Public

    Forked from CorrelAidSwitzerland/sdghackathon

    This is a project repo I forked from the sdghackathon. I produced a visualisation of the data based on the goals of the hackathon.

    HTML

  6. ScienceSeekersPsychologyBasicStats ScienceSeekersPsychologyBasicStats Public

    This is a repo to store html document for an introductory session for high school students about statistics. Link: https://kai-lim.github.io/ScienceSeekersPsychologyBasicStats/

    HTML