april 2026 update
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22
config.yml
22
config.yml
@ -20,7 +20,7 @@ languages:
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main:
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- identifier: cv
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name: CV
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url: https://github.com/pim-n/CV/blob/main/cv.pdf
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url: https://github.com/pim-n/CV/raw/main/cv.pdf
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weight: 1
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- identifier: skills
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name: Skills
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@ -34,30 +34,12 @@ languages:
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name: Contact
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url: /en/contact/
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weight: 4
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# nl:
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# languageName: ":netherlands: Nederlands"
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# weight: 2
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# contentDir: "content/nl"
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# menu:
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# main:
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# - identifier: cv
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# name: CV
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# url: /nl/cv/
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# weight: 10
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# - identifier: projecten
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# name: Projecten
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# url: /nl/projects/
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# weight: 20
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# - identifier: contact
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# name: Contact
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# url: /nl/contact/
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# weight: 30
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params:
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colorScheme: "auto"
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hidecolorschemetoggle: false
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author: "Pim Nelissen"
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info: ["Computational Physics student in Nuclear Science"]
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info: ["M.Sc. Computational Science, Physics", "Nuclear specialisation"]
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avatarURL: "images/avatar.jpg"
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since: 2024
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social:
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@ -9,7 +9,7 @@ From my background in physics and computational science, I have a strong foundat
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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.
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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.
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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.
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{{< notice tip >}}A selection of code can be found on my [git instance](http://git.pimnel.com/pim).{{< /notice >}}
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