Curriculum vitae

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Short introduction

Since September 2023, I am employed as an INRAE Plant Research Scientist (“Chargé de Recherche”) working at the Institute for Genetics, Environment and Plant Protection (UMR IGEPP) in Le Rheu (Rennes, Brittany, France). My aim is to understand the genetics and molecular basis of Pisum sativum (pea) and Vicia faba (faba bean) resistance to aphids from the Acyrthosiphon pisum and Aphis fabae species. This knowledge should help to create cultivars less susceptible to aphids and aid to augment the cultivated area of leguminous species helping in turn agriculture to become more sustainable.

From January 2019 to May 2023, I was working as a full time Data Scientist at the University of Amsterdam working closely with early career plant researchers at the Swammerdam Institute for Life Sciences. I helped fellow scientists on all aspects of data from Research Data Management, “Omics” Data Analysis to applications of Machine Learning/Deep Learning to find leads or speed up tedious tasks (e.g. counting objects from images).

To promote best practices in scientific programming and promote Open Science, I lead a small community of programming scientists that aimed to organise training courses and co-developped tools. This community is called the “Amsterdam Science Park Study Group” has a dedicated Slack workspace, a custom-made website and was awarded twice by the Dutch Research Council (NWO) in 2020 and 2021. It is still currently active by board members.

Research experience

  • September 2023 - Present: INRAE Plant Research Scientist - IGEPP, Le Rheu (France).
  • January 2019 - May 2023: Plant Researcher and Support Data scientist - University of Amsterdam, Swammerdam Institute for Life Sciences (The Netherlands)
  • May 2017 - December 2018: Plant Researcher and Data Manager - University of Amsterdam, Swammerdam Institute for Life Sciences (Amsterdam, The Netherlands)
  • May 2014 - April 2017: Postdoctoral fellow - University of Amsterdam, Swammerdam Institute for Life Sciences (Amsterdam, The Netherlands)
  • May 2010 - May 2014: Postdoctoral fellow - Jean-Pierre Bourgin Institute (Versailles, France)
  • October 2006 - December 2009: PhD in Plant Molecular Biology - University of Montpellier (France)

Education

  • PhD in Plant Molecular Biology, University of Montpellier (December 2009).

Courses undertaken

Expertise

  • Machine Learning in Python:
    • Data Transformation and Explorative Data Analysis (Pandas, seaborn).
    • Machine Learning in Python with scikit-learn.
    • Object Detection in images (Deep Learning/PyTorch).
    • Basic image processing with Pillow and scikit-image.
  • Bioinformatics:
    • DNA-Seq.
    • RNA-seq: small RNAs and messenger RNAs.
    • Variant Calling on diploid species (freebayes).
    • QTL and GWAS analysis with R (r/qtl2, rrBLUP, rainbowR).
    • Genome brower setup (JBrowse)
    • Pipeline development with Snakemake.
  • Python package development:
    • Object-oriented programming: classes, modules, functions.
    • Dependency management with poetry.
    • Testing with pytest.
    • Documentation with sphinx.
    • CI/CD using GitHub actions.
  • Version control:
    • git
    • Github.
  • Data analysis in R:
    • Data transformation and visualisation with tidyverse.
    • Exploratory data analysis: PCA, heatmaps, advanced plotting with ggplot.
    • Unsupervised analysis: PCA, clustering.
    • Linear, generalised and regularised regressions. (elastic net).
    • Survival analysis (survminer)
  • Docker containers:
    • Building of custom containers.
    • Cloud deployment.

Teaching and training activities

Courses at the University of Amsterdam

  • March 2023: Tools in Molecular Data Analysis (5224TIMD3Y). 22 students (2nd year Master students). RNA-seq lesson material development, cloud setup (virtual machines) and online teaching (24h).
  • February 2023: Keystone Project III: Big Data (5042KPIB6Y). 51 students (2nd year Bachelor Biology). RNA-seq lesson material development and teaching (12h).
  • March 2022: Tools in Molecular Data Analysis (5224TIMD3Y). 23 students (2nd year Master students). RNA-seq lesson material development, cloud setup (virtual machines) and online teaching (24h).
  • February 2022: Keystone Project III: Big Data (5042KPIB6Y). 46 students (2nd year Bachelor Biology). RNA-seq lesson material development and teaching (12h).
  • October 2021: Advanced Forensics (5274ADFB6Y): 16 students (2nd year Master students). Introduction to R and multivariate data analysis with R. Teaching (16h).
  • March 2021: Tools in Molecular Data Analysis (5224TIMD3Y). 20 students (2nd year Master students). RNA-seq lesson material development, cloud setup (virtual machines) and online teaching (24h).
  • February 2021: Keystone Project III: Big Data (5042KPIB6Y). 59 students (2nd year Bachelor Biology). RNA-seq lesson material development and teaching (12h).
  • October 2020: Advanced Forensics (5274ADFB6Y): 20 students (2nd year Master students). Introduction to R and multivariate data analysis with R. Teaching (9h). Fully online (cloud computing).
  • April 2020: Tools in Molecular Data Analysis (5224TIMD3Y). 16 students (2nd year Master students). RNA-seq lesson material development, cloud setup (virtual machines) and online teaching (24h).
  • February 2020: Keystone Project III: Big Data (5042KPIB6Y). 48 students (2nd year Bachelor Biology). RNA-seq lesson material development and teaching (12h).
  • October 2019: Advanced Forensics (5274ADFB6Y). 16 students (2nd year Master students). Lesson development on RNA-seq and statistical design, introduction to R and support on research project proposal writing. Teaching (6h).

Official Carpentries and Carpentry-style workshops (two days each)

Other workshops

  • July 2021: Co-organization and teaching at a one-week bioinformatic course organised by the Experimental Plant Sciences Graduate School. One day of online teaching on RNA-seq. 40 participants (PhD level).
  • June and July 2021: Co-organization of the first Amsterdam Science Park Study Group Summer School. Two weeks of online training in R, Python, RNA-seq, Geospatial data analysis and 16S rRNA microbiome. Around 60 non-redundant participants.
  • 2019-03-07: RNA-Seq data analysis. Organizer and instructor. University of Amsterdam (NL).
  • 2017-12-17: Snakemake day 2017 in Amsterdam (NL). 24 attendees. Co-organizer.
  • 2016-11-12: 10th anual Experimental Plant Sciences (EPS) Graduate School workshop on Plant-Insect Workshop, Leiden. Co-organizer.

Community building and guidance

Since 2017, I coordinate a small group of biologists willing to make progress in scientific programming (data visualisation, genomics, statistics, etc.). It is called the Amsterdam Science Park Study Group. Together with recruitment of new members and contributors, I co-organize code-related events for computational biologists such as Carpentry workshops, Summer Schools or I make sure that regular one-hour sessions take place (every two weeks) and participate in lesson development.

More info here: https://www.scienceparkstudygroup.info/. and on my Events page.

Peer reviewer

  • Member of the Editorial Board of Elsevier Data in Brief (2019-2020).
  • Peer-reviewer for different journals: PLoS One, Plant Science, Plant Physiology, New Phytologist.

Workshop animation and participation

  • 2021-05-27: NWO Life Conference. “The Do’s of Team Science”. Link to the workshop.
  • 2020-10-10: Panel discussion at the Team Science symposium organised by Young Science In Transition.
  • 2019-06-24: Building domain-specific local and global Carpentries communities. Carpentry Connect 2019. Manchester, UK.
  • 2018-10-02: DTL Communities at work: Research Software Engineers

Awards