Merge pull request 'update' (#1) from test-actions into main

Reviewed-on: #1

.gitea/workflows/deploy-hugo.yaml

@@ -0,0 +1,24 @@
+name: Deploy Hugo Site
+
+on:
+  push:
+    branches:
+      - test-actions
+
+jobs:
+  deploy:
+    runs-on: self-hosted
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Setup Hugo
+        uses: peaceiris/actions-hugo@v2
+        with:
+          hugo-version: '0.147'  # specify your Hugo version
+
+      - name: Build Hugo site
+        run: hugo --destination /home/pim/website-live
+
+      - name: Sync to live
+        run: rsync -av --delete ./public/ /home/pim/website-live/

config.yml

@@ -20,7 +20,7 @@ languages:
       main:
         - identifier: cv
           name: CV
-          url: https://git.pimnel.com/pim/CV/raw/branch/main/cv.pdf
+          url: https://github.com/pim-n/CV/blob/main/cv.pdf
           weight: 1
         - identifier: skills
           name: Skills

content/en/contact.md

@@ -5,4 +5,4 @@ slug = "contact"
 
 Email: pi0274ne-s@student.lu.se
 
-Phone: See my [CV](https://git.pimnel.com/pim/CV/raw/branch/main/cv.pdf).
+Phone: See my [CV](https://github.com/pim-n/CV/blob/main/cv.pdf).

content/en/skills.md

@@ -9,9 +9,9 @@ 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.
 
-My master degree thesis will be on furthering the development of a Bayesian algorithm for multisource detection in mobile gamma spectroscopy.
+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.
 
-{{< notice tip >}}A selection of code can be found on my [git instance](http://git.pimnel.com).{{< /notice >}}
+{{< notice tip >}}A selection of code can be found on my [git instance](http://git.pimnel.com/pim).{{< /notice >}}
 
 ---