Netherlands eScience Center

OPEN CALL! We're thrilled to be announcing the 2025 Open eScience Call. If you are a researcher looking for support from a Research Software Engineer (RSE) for your research project, submit your proposal by 13 October. Learn more here: www.esciencecenter.nl/calls-for-pr...

Could AI be (in) FAIR? Open Science is driven by FAIR principles. Made for data, adapted for software, how can they survive the current wave of "Artificial…

In our newest blog, Carsten reminds us: FAIR principles still matter — maybe more than ever. AI can sound smart, but if we can’t find, check or reuse what it spits out, is it science or just a fancy remix? Read the full breakdown here:

Scientific Community Building through Workshops: the NPLinker eScience experience A blog post by Wageningen University & Research Assistant Professor Justin van der Hooft

In this blog post, @jjjvanderhooft.bsky.social reflects on the challenges and lessons learned from organizing a computational omics workshop in @w-u-r.bsky.social

Empirically evaluating privacy in machine learning III: functional & gaussian differential privacy Using statistics to think like a hacker, so we can avoid them!

Part 3 discusses reformulations of differential privacy that are useful for verifying differentially private machine learning: blog.esciencecenter.nl/empirically-...

Empirically evaluating privacy in machine learning II: Hypothesis testing Using statistics to think like a hacker, so we can avoid them!

How can we verify privacy in data releases? Flavio Hafner's series on privacy and machine learning continues:

Part 2 shows how differential privacy constrains the extent to which a hacker can find out about single records from a private data release: blog.esciencecenter.nl/empirically-...

For our latest #SoftwareSpotlight, we're featuring MUSCLE3, a software that helps scientists connect computer models to work together. This is useful when studying complex systems—like climate change, energy grids or the human body.

Learn more here:
research-software-directory.org/software/mus...

Keeping your scientific data files small An RSE’s guide to NetCDF compression

Are your research datasets eating up terabytes of valuable storage space? In our latest blog, our RSE, Bart, explains compression techniques for NetCDF files that can reduce storage needs. Learn how these methods can save space and reduce your carbon footprint: blog.esciencecenter.nl/keeping-your...

Solving the mystery of the missing symbols! (part II) In that earlier post, we were investigating why the MingW-w64 build of DuckDB fails to export the C-API symbols in the final DLL. We identified that the issue was introduced by the commit d1ea1538…

In his second installment of our investigative series, Suvayu delves deeper into the enigmatic case of missing symbols that can perplex developers. 🕵️‍♂️

Discover how advanced debugging tools can shed light on these elusive issues.

Read the full blog here:

Fellow Feature: Peter-Paul Zwetsloot - eScience Center Learn more about the progress of the project, 'Mental Health Research Software ’ led by Henk Cremers.

In our last #FellowFeature, we are showcasing the project from @ppmzwetsloot.bsky.social. Peter-Paul is exploring whether a federated learning infrastructure is feasible for the future national cardiomyopathy register. Learn more about his project here.

In the latest blog, we learn how the open-source benchmark compares training speed across different supercomputers, including secure environments. Key takeaways? Hardware differences drive performance gaps and multi-GPU scaling is efficient. Learn more:

Fellow Feature: Henk Cremers - eScience Center Learn more about the progress of the project, 'Mental Health Research Software ’ led by Henk Cremers.

We are excited to share Dr. Henk Cremers as the latest #FellowFeature. As an Asst. Prof. at the @uva.nl Clinical Psychology program, Henk's focuses project focuses on mental health research software that makes data more accessible.

Read more about his project:

Introduction to Deep Learning with Python Written by Sven van der Burg, Carsten Schnober, Sarah M. Brown and Toby Hodges

Over the past years, eScience Center RSEs have worked on lesson materials for the 'Introduction to Deep Learning course. Now, the lesson is published in The @carpentries Lab. Read about the lesson and our experience with the process in this blog! #deeplearning

What if you could analyze sensitive data without ever moving it? 🤯 That’s exactly what Vantage6 does! This powerful tool sends the analysis to where the data lives—keeping everything secure and private.

Developed by experts at IKNL, Maastricht University and the eScience Center!

Professional Paths for Research Software Engineers How can Dutch research institutions maintain a competitive edge in an increasingly commercial and digital research landscape?

Curious about the main challenges and opportunities for RSEs in the Netherlands? Eager to support the professionals in these roles? Join the NL-RSE webinar tomorrow!

A debugging journey into the unknown (part I) Faced with a buggy library, most people will just give up and wait for a patch to be released. Certainly not our engineers.

Faced with a buggy library, most people will just give up and wait for a patch to be released. Certainly not our engineers. Check out RSE Suvayu's debugging journey in our latest blog:

On 21 March, KB Lab will host a conference in collaboration with the Semantics of Sustainability project. RSEs Carsten Schnober and Angel Daza have helped develop advanced machine learning applications for the analysis of historical data in this project.

Fellow Feature: Stefan Kirsch - eScience Center Learn more about the progress of the project, ‘Turtle and Hare Workshops: Exchanging software skills from beginner to experienced’ led by Mara Bialas

Meet Stefan Kirsch, an eScience Center Fellow dedicated to making research software more sustainable! In his fellowship, he focuses on improving software best practices in the scientific community.

Still using MATLAB but want to make your models more shareable? In our latest blog, Bart Schilperoort explores how containerizing MATLAB Runtime with Docker makes it easier to run and share MATLAB applications—without needing a MATLAB license! Check it out: blog.esciencecenter.nl/sharing-matl...

Empirically evaluating privacy in machine learning I: Introduction Research in the social and health sciences often relies on accessing data sourced from statistical agencies or healthcare organizations…

Why would anyone tell a researcher truthfully about breaking the law? 'Randomized response' uses coin flips to provide plausible deniability. Check out this blog by Flavio Hafner on how differential privacy protects sensitive data while enabling researchers to gain insights!

Fellow Feature: Tina Rozsos - eScience Center Learn more about the progress of the project, ‘Turtle and Hare Workshops: Exchanging software skills from beginner to experienced’ led by Mara Bialas

Meet Tina Rozsos! From championing Open Science to bridging the gap between research and technology, Tina is making waves in the scientific community! In our latest #FellowFeature, she shares insights on her work, passion for reproducible research and the impact of collaboration.

Meet Rosemary! This web-based application, developed by the eScience Center in collaboration with CLARIAH, provides an accessible interface to explore public Linked Data—no SPARQL knowledge needed. #SoftwareSpotlight

FAIR principles: 5000 years of common sense The FAIR acronym stands for Findable, Accessible, Interoperable and Reusable. If you are a researcher, certainly you’ve heard about FAIR…

Making your data and code FAIR may sound like a new extra responsibility. But, is it new? Check out what Pablo Rodríguez-Sánchez has to say in our most recent blog.

Machine Learning in Python with Scikit-learn This workshop will provide participants with the basics of machine learning in Python.

Registration closes 3 March! Don't miss the opportunity to take this workshop taught by experts on Machine learning in python with scikit-learn.
Sign up today!

Machine Learning in Python with Scikit-learn This workshop will provide participants with the basics of machine learning in Python.

🚀 Ready to dive into Machine Learning with Python? Join us for the Machine Learning in Python with scikit-learn workshop! Enhance your skills with practical learning and expert guidance.

Don't miss out—register now! 👉 buff.ly/41nKsMn
#MachineLearning #Python #DataScience"

Meet Mara Bialas in this week's #FellowFeature. She is leading Turtle and Hare Workshops (TAHWS), a platform connecting beginner software users ("turtles") with advanced users ("hares") to exchange open-source software skills.🐢 🐰

Meet Yorben Lodema, our next #FellowFeature and a PhD candidate at Utrecht UMC!

Yorben is on a mission to make electroencephalography (EEG) processing more accessible to clinical researchers. Read more:

Reproducible research with The Turing Way The Netherlands eScience Center and Turing Way have long been collaborating on the common goal to improve reproducible research practices

The @turingway.bsky.social is collecting positive impact stories - here's ours, written by Carlos Martinez. If you would like to share your own positive impact story, you can do that here: https://buff.ly/4aNIwQl

Fellow Feature: Anne Mickan - eScience Center Learn more about the progress of the project, ‘T Grand-challenge.org: making AI application benchmarking for medical diagnostics accessible to the public’ led by Anne Mickan

We've got another #FellowFeature coming your way. This time, we're highlighting the project from Anne Mickan, a research software engineer at Radboud UMC. Learn more about how she is making medical diagnostics accessible to the public!

The Carpentries Instructor Training The Instructor Training is hands-on throughout: short lessons alternate with practical exercises, including practice teaching sessions

Interested in becoming a certified Carpentries Instructor? Join the training from 4-5 March! The training will be held online and registration closes 24 February!

In this month's #SoftwareSpotlight, we're featuring Speckcn2, a Python package designed by the eScience Center and TU Delft to revolutionize laser-based satellite communications. Using machine learning to analyse star twinkling patterns, it estimates atmospheric turbulence.
https://buff.ly/3E91yo2