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: Support Data scientist & Data Manager - University of Amsterdam, Swammerdam Institute for Life Sciences (The Netherlands)
  • May 2017 - Present: Data scientist & Data Manager - University of Amsterdam, Swammerdam Institute for Life Sciences (The Netherlands)
  • May 2014 - April 2017: 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

  • 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 Biologie). 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 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)

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.

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 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 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

PDF version

To download my CV in PDF please click here