Curriculum vitae

Short introduction

I am a support data scientist at the University of Amsterdam (Swammerdam Institute for Life Sciences) helping fellow researchers on Research Data Management and Data Analysis. On a daily basis, I work mostly with Plant Scientists that are struggling with various (plant) genomics and other “omics” issues. I also participate in a pilot project at the University of Amsterdam to implement the iRODS Open Source Data Management Software together with a graphical use interface called “YODA” developed by the University of Utrecht.
To reach out to more scientists and gather a community of computational life scientists, I also coordinate a Mozilla Study Group called the “Amsterdam Science Park Study Group”.
Last but not least, I am an official Software and Data Carpentry Instructor from the Carpentries Foundation. As such, I regularly organise scientific programming and data analysis workshops for researchers to teach them good practices in programming and data science.

Research experience

  • Jan 2019 - Present: Data scientist & Data Manager - University of Amsterdam, Swammerdam Institute for Life Sciences (The Netherlands)
  • May 2014 - May 2018: Postdoctoral fellow - University of Amsterdam, Swammerdam Institute for Life Sciences (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

  • Scientific programming in Python:
    • Data import and transformation with Pandas.
    • Machine Learning in Python with scikit-learn. Regularized Regressions and Random Forests.
    • 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.
  • Version control: git and 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

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 Biologie). 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)

November 2019: Two-day R and Open Science workshop in Amsterdam (NL). 20 attendees. Organizer and instructor.
February 2019: Two-day Data Carpentry Genomics workshop in Wageningen (NL). 35 attendees. Instructor.
January 2019: Two-day Software Carpentry workshop in Amsterdam (NL). 24 attendees. Co-organizer and instructor.
December 2017: Two-day Data Carpentry Genomics workshop in Amsterdam (NL). Co-organizer and teaching. 26 attendees. Organizer and instructor.
October 2016: Two-day Software Carpentry workshop in Amsterdam (NL). 25 attendees. Co-organizer and helper.

Other workshops

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.

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 “Amsterdam Science Park Study Group” and is officially linked to the Mozilla Science Lab organisation. I make sure that regular one-hour sessions take place (every two weeks) and participate in lesson development. Sessions can also be longer (afternoons) to dive further into a topic of interest. Furthermore, I regularly organise two-day Carpentries Foundation workshop as part of the Amsterdam Study Group activities.
More info here: https://www.scienceparkstudygroup.info/.

Peer reviewer

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

Publons profile: https://publons.com/researcher/3169958/marc-galland/

Workshop animation

2018-10-02: DTL Communities at work: Research Software Engineers
2019-06-24: Building domain-specific local and global Carpentries communities. Carpentry Connect 2019. Manchester, UK.

Presentations at international conferences

2019-08-28: A tomato Lipid Transfer Protein in trichomes. R. Kortbeek, M. Galland, I. Maoz, R. Schuurink, N. Dudareva, P. Bleeker. Terpnet 2019 conference, Halle, Germany.

PDF version