diff --git a/_data/sessions.yml b/_data/sessions.yml
index 703c1b5..6589aa1 100644
--- a/_data/sessions.yml
+++ b/_data/sessions.yml
@@ -229,7 +229,7 @@
   subtype: Workshop
   service:
   hidden: false
-  description: Make your code go fast, fast - practical performance engineering for research software.<br>Whether you're running massively-parallel computer simulations or processing huge amounts of research data, research software across all domains increasingly requires the use of large-scale data and computational resources. As a result, it's becoming increasingly important to be able to write fast, well-optimised code to ensure efficient use of computational resources such as high-performance computing clusters, as well as improved turnaround time on research outcomes. Simply put, time spent waiting for code to run is time not spent doing research. Squeezing every available bit of performance out of your code can be extremely time-consuming, but fortunately you can go a long way with just a little bit of programming know-how applied in the right places. This talk will provide an introduction to performance engineering, with a focus on practical, well-tested techniques for both compute- and data-heavy workflows. I will discuss methodologies and open-source tools which will help you get the most "bang for your buck" when optimising slow code in your research pipelines.
+  description: <p>Make your code go fast, fast - practical performance engineering for research software.</p><p>Whether you're running massively-parallel computer simulations or processing huge amounts of research data, research software across all domains increasingly requires the use of large-scale data and computational resources. As a result, it's becoming increasingly important to be able to write fast, well-optimised code to ensure efficient use of computational resources such as high-performance computing clusters, as well as improved turnaround time on research outcomes. Simply put, time spent waiting for code to run is time not spent doing research.</p><p>Squeezing every available bit of performance out of your code can be extremely time-consuming, but fortunately you can go a long way with just a little bit of programming know-how applied in the right places. This talk will provide an introduction to performance engineering, with a focus on practical, well-tested techniques for both compute- and data-heavy workflows. I will discuss methodologies and open-source tools which will help you get the most "bang for your buck" when optimising slow code in your research pipelines.</p>
 -
   title: Keypoint workshop
   themes: []