diff --git a/config.yml b/config.yml
index f0668bb..0f47bee 100644
--- a/config.yml
+++ b/config.yml
@@ -20,7 +20,7 @@ languages:
       main:
         - identifier: cv
           name: CV
-          url: https://github.com/pim-n/CV/blob/main/cv.pdf
+          url: https://github.com/pim-n/CV/raw/main/cv.pdf
           weight: 1
         - identifier: skills
           name: Skills
@@ -34,30 +34,12 @@ languages:
           name: Contact
           url: /en/contact/
           weight: 4
-  # nl:
-  #   languageName: ":netherlands: Nederlands"
-  #   weight: 2
-  #   contentDir: "content/nl"
-  #   menu:
-  #     main:
-  #       - identifier: cv
-  #         name: CV
-  #         url: /nl/cv/
-  #         weight: 10
-  #       - identifier: projecten
-  #         name: Projecten
-  #         url: /nl/projects/
-  #         weight: 20
-  #       - identifier: contact 
-  #         name: Contact
-  #         url: /nl/contact/
-  #         weight: 30
 
 params:
   colorScheme: "auto"
   hidecolorschemetoggle: false
   author: "Pim Nelissen"
-  info: ["Computational Physics student in Nuclear Science"]
+  info: ["M.Sc. Computational Science, Physics", "Nuclear specialisation"]
   avatarURL: "images/avatar.jpg"
   since: 2024
   social:
diff --git a/content/en/skills.md b/content/en/skills.md
index 49ebc65..eb51eee 100644
--- a/content/en/skills.md
+++ b/content/en/skills.md
@@ -9,7 +9,7 @@ From my background in physics and computational science, I have a strong foundat
 
 I am particularly interested in using those skills for peaceful applications of nuclear science. My [bachelor degree thesis](http://lup.lub.lu.se/student-papers/record/9168893) was about applying machine learning on radioactive decay data. I am proficient in Python, experienced with R and MATLAB, and have some exposure to C++, C# and SQL. I am very comfortable with GNU/Linux and Git workflows.
 
-I am currently working on my masters thesis. In the first half of my masters thesis I have developed PG-RAD, a Python simulation tool for generating realistic mobile gamma spectrometry data that mimics real-world data. It is particularly useful for simulating localization scenarios of radioactive point sources using car-borne spectrometry setups. In the second half of my thesis, I am using the generated data to quickly generate various scenarios, in order to test Bayesian source localization algorithms for their effectiveness at localizing sources as a function of source activity, source distance from the road, and more.
+I am currently working on my masters thesis. In the first half of my masters thesis I have developed [PG-RAD](http://github.com/pim-n/pg-rad), a Python simulation tool for generating realistic mobile gamma spectrometry data that mimics real-world data. It is particularly useful for simulating localization scenarios of radioactive point sources using car-borne spectrometry setups. In the second half of my thesis, I am using the generated data to quickly generate various scenarios, in order to test Bayesian source localization algorithms for their effectiveness at localizing sources as a function of source activity, source distance from the road, and more.
 
 {{< notice tip >}}A selection of code can be found on my [git instance](http://git.pimnel.com/pim).{{< /notice >}}
 
diff --git a/static/images/avatar.jpg b/static/images/avatar.jpg
index 34ed5ad..212fbbe 100644
Binary files a/static/images/avatar.jpg and b/static/images/avatar.jpg differ