diff --git a/content/events/2026_09_singlecellproteomics.md b/content/events/2026_09_singlecellproteomics.md
new file mode 100644
index 0000000..e08a7a8
--- /dev/null
+++ b/content/events/2026_09_singlecellproteomics.md
@@ -0,0 +1,39 @@
++++
+title = "Scverse x sc-Proteomics Hackathon 2026-09 Vienna"
+date = 2026-09-04T00:00:05+01:00
+description = "scverse x single-cell proteomics hackathon"
+link = "https://scverse.org/sc-proteomics2026/"
+draft = false
++++
+
+## Welcome
+
+Join us for the joint [scverse](https://scverse.org) x single-cell proteomics hackathon on **September 4-5, 2026** at the Vienna Biocenter in Vienna.
+
+This hackathon aims to bring together users and developers of scverse tools with mass spectrometry-based single-cell proteomics (SCP) researchers. The main topic of this hackathon will center on the specialized preprocessing and downstream analysis workflows unique to SCP data.
+
+During this hackathon, we will tackle core computational challenges, settle on robust data formats, and establish best practices for handling low-input MS signals. You will have the opportunity to directly improve existing tools, build missing pieces of the ecosystem, and optimize scverse packages for single-cell proteomics data. All contributions will be made publicly available on GitHub under an open-source license.
+
+## Hackathon Main Tasks
+
+### Task 1: Curation of Datasets
+
+Task Lead: Florian Mutschler
+
+Identifying, collecting, and preparing MS-based single-cell proteomics datasets to start a community-curated resource for testing analysis strategies and benchmarking methods such as imputation or normalization. Establishing AnnData format from the scverse ecosystem as the main object for benchmarking and analysis.
+
+### Task 2: Data QC and Preprocessing
+
+Task lead: Jose Nimo
+
+Identifying best practices for analyzing different types of MS-based single-cell proteomics datasets. Including: QC metrics, imputation strategies, normalization approaches, and methods for handling biological and technical confounders such as cell cycle, cell size, and batch effects. We aim to prototype methods in a service-styled package, to deal with these problems.
+
+### Task 3: Downstream analysis
+
+Task lead: Anna Sophie Welter
+
+Come together, think and benchmark different challenges during downstream analysis. How to perform feature selection? How can we use proteomics for cell type annotation?
+
+## Registration
+
+Please fill out the following [Luma form](https://luma.com/pwzuldwr)