.
+
+## Sheffield RSE Team
+
+The Sheffield RSE Team aims to [collaborate](https://rse.shef.ac.uk/collaboration/) with you to help improve your
+research software. They can [provide dedicated staff](https://rse.shef.ac.uk/collaboration/provision/) to ensure that
+you can deliver excellent research software engineering on your research projects.
+
+## Research IT
+
+[Research IT](https://students.sheffield.ac.uk/it-services/research) directly supports research, both academic and
+commercial. We provide large scale HPC systems, advice on everything from statistics to ML to data pipelines and
+training for both students and staff.
+
+Working with academics, our staff are embedded within research groups on both long and short term engagements.
diff --git a/_people/edwin-brown.md b/_people/edwin-brown.md
index 78dc1f23..a885f7fc 100644
--- a/_people/edwin-brown.md
+++ b/_people/edwin-brown.md
@@ -1,17 +1,20 @@
---
alumnum: false
-level: 2
+level: 1
published: true
-othernames: Edwin
+othernames: Edwin
surname: Brown
-role: Research Software Engineer
+role: Senior Research Software Engineer
---
-Edwin joined the RSE team in October 2022. He comes from a background in geophysics following a BSc and MSc in Geophysical Sciences at the University of Leeds. After university, he worked in the private sector, developing machine learning (ML) workflows to solve geophysical imaging and inversion problems.
+Edwin joined the RSE team in October 2022. He comes from a background in geophysics following a BSc and MSc in Geophysical Sciences at the University of Leeds. After university, he worked in the private sector, developing machine learning (ML) workflows to solve geophysical imaging and inversion problems.
+
+Edwin spends 50% of his time working in the Sheffield RSE team and the rest working in the Research Engineering Group (REG) at the Alan Turing Institute. Edwin has been working on a series of projects with the Sheffield Solar group in the School of Mathematical and Physical Sciences on the topic of modelling electricity demand in collaboration with various industry partners.
+
+Edwin has practical experience in the designing, training and evaluation of ML models. He is experienced in Python having worked with data science libraries such as Pytorch, Tensorflow, tranformers and XGBoost. He has a growing interest in MLOps (Machine Learning Operations) and the practical challenges of scaling up ML practices.
-Edwin has practical experience in the designing, training and evaluation of ML models. He is experienced in Python having worked with data science libraries such as Numpy, Pandas, Scikit-learn, Tensorflow and Keras. He has a growing interest in MLOps (Machine Learning Operations) and the practical challenges of scaling up ML practices.
* Email: w.e.brown (at) sheffield.ac.uk
* Github: [@EdwinB12](https://github.com/EdwinB12)
diff --git a/_people/michael-foster.md b/_people/michael-foster.md
new file mode 100644
index 00000000..98a5625a
--- /dev/null
+++ b/_people/michael-foster.md
@@ -0,0 +1,24 @@
+---
+alumnum: false
+level: 2
+published: true
+
+othernames: Michael
+surname: Foster
+role: Research Software Engineer
+
+---
+
+Michael joined the RSE team in October 2024.
+He comes from a background in Computer Science, following an integrated masters degree and PhD in software testing at the University of Sheffield.
+After that, he was a research associate on the [CITCoM project](https://sites.google.com/sheffield.ac.uk/citcom/home) in the software testing group, also at the University of Sheffield.
+During this time, he has been an active member of the software engineering research community and an advocate for good research software practice, having served as a dedicated software reviewer for several software engineering conferences.
+
+Michael's main expertise is in black-box testing of traditionally "hard to test" software through the analysis of software logs and time series data.
+He is experienced in Python, and has worked with data science libraries such as Numpy, Pandas, and Statsmodels.
+He also has experience in functional programming, formal methods, code optimisation, and parallelisation.
+
+* Email: m.foster (at) sheffield.ac.uk
+* Github: [@jmafoster1](https://github.com/jmafoster1)
+* [Google Scholar](https://scholar.google.com/citations?user=4fTJseoAAAAJ)
+* [Personal Webpage](https://jmafoster1.github.io)
diff --git a/pages/training/fair4rs/index.md b/pages/training/fair4rs/index.md
index aff9d664..5bc16c08 100644
--- a/pages/training/fair4rs/index.md
+++ b/pages/training/fair4rs/index.md
@@ -32,10 +32,6 @@ research software[^3].
## Outline of the programme
- Info! The definitive programme (with dates and registration links) will be
-online on Oct 1st.
-
-
* [Better software for better research: Introduction to the FAIR training
programme](#better-software-for-better-research-introduction-to-the-fair-training-programme), Tuesday 22nd October 2024
* [Software lifecycle planning](#software-lifecycle-planning), Friday 8th November 2024
@@ -49,11 +45,13 @@ online on Oct 1st.
#### Better software for better research: Introduction to the FAIR training programme
-**Tuesday 22nd October 2024, LunchBytes talk, 12pm, online, [registration link](https://mydevelopment.csod.com/ui/lms-learning-details/app/event/60f213bd-340d-4035-8754-a15c9567d620)**
+**Tuesday 22nd October 2024, LunchBytes talk, 12pm, online,**
In this introductory session we will try to understand what the FAIR principles are and why they have emerged. We will
then introduce some actions on how to apply them to software and present a global review of the training programme.
+Material: [Recording](https://orda.shef.ac.uk/articles/media/Better_software_for_Better_research_Introduction_to_the_FAIR2_for_Research_Software_training_programme/27283239?file=49937889) and [slides](https://fair2-for-research-software.github.io/Better_software_for_better_research/#/title-slide)
+
#### Software lifecycle planning