april 2026 update

This commit is contained in:
Pim Nelissen
2026-04-03 14:42:23 +02:00
parent 104c7796ae
commit e3a4f082a9
3 changed files with 3 additions and 21 deletions

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@ -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:
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# 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/
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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:

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@ -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 >}}

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