Organisation and membership
The Swiss Reproducibility Network (SwissRN) Academy is a group of early career researchers from Swiss universities who are interested in reproducibility, metascience, good research practices, and transparency. Our goal is improving the quality of science by sharing our knowledge of reproducible research with students and researchers. We want to create a national network among young researchers from various fields and backgrounds, that enables interdisciplinary dialogue and collaboration. We’d be happy to see our community grow!
If you are interested in these or related topics, feel free to contact us to find out how to join and contribute: SwissRN academy
Other Reproducibility Networks have established similar academies, such as the UKRN Academy.
Upcoming Events
- 7 November 2024 – Quarto & R Markdown Workshop - Geneva
In collaboration with the Center for Reproducible Science (CRS) at the University of Zurich, we will be hosting a half-day workshop dedicated to learning how to use Quarto and R Markdown tools in our own research workflow, in order to analyze, visualize and prepare manuscripts in one straightforward tool. With the help of two experts from the CRS, the theoretical background on these tools and their use in reproducible research practices will be described (virtually, open to all) and a hands-on workshop will take place where researchers can practice using the tools on their own research data (on-site at Uni Mail, places limited). If you’re interested in learning more, reach out to the organizers at nocelaboratory@unige.ch or sign up for either part (virtual introduction and/or the on-site workshop at Uni Mail) here: https://forms.gle/rfSoDZMcTXXXQ9xj7
Past Events
11 June 2024 – ReproHack at the Swiss Reproducibility Conference 2024 - Zurich
During this Reproducibility Hackathon held at the Swiss Reproducibility Conference 2024, participants attempted to reproduce results from published research papers with openly available code and data. Read more about the insights from the event in our report.
2 May 2024 – Swiss Reproducibility Network Academy meets Cancer Research Network Bern – Bern
In collaboration with the Open Science Team of the University Library of Bern, we will be hosting two short talks at the Cancer Research Network Bern on Thursday May 2nd, 2024 from 13:00-14:00, online via Zoom and on-site. Dr. habil. Olga Churakova (Data Steward: Medicine and Veterinary Medicine, University of Bern) will talk about research data management and Peter Methys Degen (PhD Candidate Bioinformatics, University of Bern) will talk about researcher degrees of freedom in the analysis of Single-cell RNA-Sequencing data.
6 December 2023 – Talk with Prof. Nicolas Langer: “Bringing Open and Reproducible Science into a Successful Career” – University of Zurich / Online
The SwissRN Academy hosted a talk by Prof. Dr. Nicolas Langer who shared his experiences with open science, its challenges and benefits, and how it is shaping his career. He also shared his tips on reproducibility and how he promotes open science in his lab.
21 November 2023 – Social Meeting – Zurich
Members of the SwissRN Academy gathered in Zurich to chat about open science and reproducibility while enjoying Glühwein.
10 October 2023 – Social Meeting – Zurich
Members of the SwissRN Academy gathered in Zurich to chat about open science and reproducibility.
20 May 2022 – Swiss ReproHack – University of Bern
The SwissRN Academy hosted the first national Reproducibility Hackathon, and talks by Mark Robinson, Anja Eggert, and Tim Errington.
25 February 2022 – SwissRN Academy First Meeting – Online
The SwissRN Academy hosted an online event with two presentations, networking and discussion of future activities.
Finishing up my Master’s in Psychology at UZH, I feel that open science practices have been part of my work and studies ever since. There is a strong effort in my field to improve research methods and reflect on given standards. I plan to start my PhD in the US next year and would love to continue my academic journey in the field of metascience. I have a deep interest in improving methods and theories in scientific psychology. |
Ursa has a PhD in Marketing and Management and is currently a Postdoctoralresearcher at CEPE, ETH Zürich. During her PhD, she was interested in open science practices in marketing and management journals, and worked on prosocial behavior, inequality perception, and developing more objective marketing measures. Currently, she is dedicated to conducting preregisteredRandomized Controlled Trials (RCTs) to increase sustainable behavior. Ursa’s commitment to open science is evident as she preregisters all her studies and readily shares data, code, and experiment scripts on the Open ScienceFramework (OSF). Furthermore, she has actively joined the Swiss ResearchNetwork (SwissRN) to advocate for these principles among her colleagues. |
I am a psychologist and PhD student at the Institute of Computational Linguistics, working on neural auditory processing in older adults with varying hearing and cognitive abilities. In this context, I have learned a lot about signal and data processing and computational modeling, as well as writing processing pipelines and acquiring data. Since I have also benefited a lot from the open work of others and want to make my scripts and data accessible myself, I am happy to exchange ideas with people who are interested in exactly that. In the field of neuroscience and psychology, the reproducibility crisis is a big topic and I am very interested in solutions and strategies to solve this problem in the longer term. |
Only 9% of plastic waste is recycled worldwide, despite existing technologies to do so. As part of the Global Health Engineering group at ETH Zurich, my research seeks to engineer solutions that work in low-resource contexts. Open-science and reproducibility can facilitate multiplier effects of plastic recycling solutions, especially in low- and middle-income countries. In pursuit of this, I aim to provide transparency and credit to the people and methods that contribute to my PhD research. |
I am a PhD student at the University of Bern, under the supervision of Prof. Hanno Würbel. Our research project will investigate how inbreeding impacts developmental robustness and stress resilience in mice, with a focus on its implications to animal welfare and replicability of research. I believe that replicability is a cornerstone of science, separating evidence from anecdotes. It is essential for maintaining the quality of our research and public trust in our findings. |
In my first project as a PhD student in bioinformatics, I performed data-driven simulations to investigate the replicability of bulk RNA sequencing experiments in the presence of small cohorts and population heterogeneity. My current work as a senior PhD student focuses on the robustness of single-cell RNA-Seq analysis results under variation of computational pipelines. As my projects are closely related to meta-scientific research, I’m happy to have discovered an active network of early-career researchers interested in principles of open science, reproducibility, and replicability. |
I am a researcher with a PhD in Developmental Psychology from the University of Amsterdam. In my research I used different non-invasive neuroimaging techniques (electroencephalography, magnetic resonance imaging) and methodological approaches (e.g., computational models) to study audiovisual learning in children and adults. In Zurich I worked at the Department of Child and Adolescent Psychiatry and Psychotherapy and at the Neurolinguistics group in the Psychology Department. My current focus is on using my experiences with diverse types of data, methodologies, and researchers to improve reproducibility and open science. |
I am an evolutionary biologist and PhD student at the University of Basel, working on trying to understand the causes of adaptation through a genomic and developmental biology standpoint. Working with genomic data makes me confront the complexity of handling enormous datasets and long pipelines that have to be communicated in a transparent way to guide other researchers through the process that leads to a particular conclusion. I find the Swiss Reproducibility Network Academy a good environment to learn and exchange ideas on how to improve our practices as researchers and bring transparency and analytical and computational reproducibility to our fields. |
I am interested in regression modelling and best practice in medicine mostly for observational data. This includes the selection of variables, transformations, competing risk methodology as well as the use of p-values and alternatives. |
I am a psychologist beginning my PhD at the University of Bern, focusing on the intersection of psychology and cybersecurity. In my research, I am particularly interested in supporting professionals in privacy and cybersecurity. The interdisciplinary nature of my field makes synthesizing and reproducing results challenging. For me personally, my methodological training has always emphasized the importance of reproducibility in research. Now, I aim to improve methods of psychological research in the realms of cybersecurity and privacy. |
I hold a Master’s degree in neuroscience and work as a data manager within the Psychiatry Research and Teaching Platform of the University Hospitals of Geneva (HUG) where I advise doctors on the management of their data. I am currently writing a PhD project due to start next year on how to improve reproducibility in medical science through good data management practices. My previous research concentrated on fMRI and schizophrenia patients. Generally speaking, reproducibility, data sharing, and FAIR data are topics that interest me. My goal is to raise awareness of good research practices to improve the quality and transparency of medical research. |
I am a neuroscience PhD student with a background in biology and neuropsychology. Before my PhD, I worked as a neuroimaging data assistant in two different countries and noticed the difficulty in streamlining imaging procedures across sites, cities, and countries… this led to my initial interest in open science, as I wanted to make imaging pipelines and procedures as transparent as possible through proper documentation and data/code dissemination. Currently, I research the temporal dynamics of multilingual semantic knowledge and co-organize ReproducibiliTea journal clubs in Geneva with the local SwissRN node. |
A medical doctor with a Masters in Nanosciences and Nanotechnologies as well as a Masters in Epidemiology and a PhD in the field of clinical trials. Having a great interest in reproducible research and techniques for optimising open science in research projects. |
I am currently in the final stages of my PhD in Biostatistics. My research focuses on methodological aspects of replicability. Specifically, I am developing new methods for the design and the analysis of replication studies. My PhD journey made me realize the importance of good research practices, reproducibility and transparency. Furthermore, I am a strong advocate of open science and believe that research outputs should be available to everyone. |
I am a PhD student in cognitive neuroscience with a background in psychology. The first year of my PhD made me realize the importance of reproducible science practices, as I was faced with an enormous pile of published but incomparable study procedures. A large portion of deviations between study procedures arises from the lack of openly accessible assessment tools, which facilitate assessment standardization. This issue led me to my current project: I am developing a multilingual, open-access, and open-source working memory test battery in Python. As part of the SwissRN I hope to collaborate with like-minded researchers to contribute to the corpus of transparent open-access research tools within science. |
I am a trained statistician with a PhD in Epidemiology and Biostatistics. During my PhD I worked on statistical methodology for the design and analysis of replication studies. I am generally interested in statistics, meta-research and their intersection. My current work includes statistical research for evidence assessment and meta-research on methodological research, for example, on the reporting of simulation studies. I believe that transparency and openness are essential for the credibility of research. I try to make my research reproducible and openly available, and to promote these principles among my colleagues and peers. |
I am a second-year PhD student at the University of Basel (CH), focusing on muscle physiology and biomechanics. My research develops openly available automatic image analysis methods to evaluate muscle geometry and its adaptation to training and ageing. I care about open science and reproducibility because they promote transparency, which is crucial when working with images. Sharing image data and analysis methods ensures that findings can be verified and built upon, which is vital in advancing our understanding of muscle adaptation to health and disease. |
As a dedicated Research Fellow at the Center of Reproducible Science, I am committed to advancing the field of animal welfare and scientific rigor. My work primarily focuses on advancing systematic review methodology, emphasizing the critical importance of reproducibility in research. My team and I are working on the development of automated systematic review methodologies, aiming at facilitating the way we synthesize scientific evidence. Furthermore, our research aims at improving the translation of findings from animal studies to human therapies in neuroscience. My passion lies in fostering a culture of transparency, rigor, and ethical considerations, ultimately contributing to the enhancement of scientific practices and the betterment of society. |
My name is Chhavi Sachdeva, and I am currently a junior postdoctoral researcher at UniDistance Suisse, under the supervision of Prof. Dr. Nicolas Rothen. My research focuses on the link between visual perception and memory, using healthy special populations as my sample. I believe that the purpose of research is to benefit both other researchers and the general public. This is why I advocate for science to be both reproducible and open—reproducible so we can trust research, and open so it is accessible to a wider audience. |
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