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# Hardskills
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Welcome to the hardskills section of my portfolio. This is where I list the concrete technical skills I've built. Unlike soft skills, these are measurable and testable.
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Welcome to the hardskills section of my portfolio. This is where I list the
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concrete technical skills I've built. Unlike soft skills, these are measurable
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and testable.
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---
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<br>
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## Python programming
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**Overview:**
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Core language for my data science and bioinformatics workflows. Used daily for data wrangling, statistical analysis, and modeling.
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**Key Strengths:**
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- Experienced in scikit-learn, PyTorch, XGBoost
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- Solid understanding of OOP, scripting, and automation
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- Focus on writing reproducible, clean code (PEP8, modular design)
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**Use Cases:**
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Whenever I work with machine learning, I use Python as the to go language
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for that. Further, I wrote a Python package that allows to train a special
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type of interpretable neural network that has the architecture of a
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molecular network (not yet made available publicly at the time of writing this).
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---
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<br>
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## R programming
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**Overview:**
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Core language for my data science and bioinformatics workflows. Used daily for data wrangling, statistical analysis, and modeling.
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**Key Strengths:**
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**Use Cases:**
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- Programming of the SplineOmics package (see section: software-packages).
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R is the number one language in bioinformatics and therefore I use it a lot
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in my daily work. I did a multitude of statistical analyses with it, and
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also wrote an R package, SplineOmics (see section: software-packages).
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## Presenting
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**Overview:**
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Presenting results and topics is a key skill when someone pursues a scientific education. Since highschool, I had to make many different presentations, which includes more formal ones at seminars and conferences, but also more informal ones in group meetings
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