Beschreibung

Python Developer | Web Scraping & Image Analysis

I build robust Python back-ends to automate data extraction and image analysis, turning complex sources into structured data.

• Web Scraping: Using Playwright and BeautifulSoup, I develop custom scrapers that navigate JavaScript, login walls, and complex sites to extract clean, organized data—like automating the collection of 12 key parameters from 700+ EU project reports

• Image Analysis: With OpenCV, ImageJ, and AI models like StarDist, I create solutions for quantitative analysis—from detecting and measuring specific objects (e.g., chloroplasts in 3D imagery) to calculating metrics like leaf coverage across large datasets

I deliver tools that integrate into workflows, save you time and reduce manual error. Let’s discuss how I can help with your next data or image analysis project.

Branchenexpertise

Sprachen

Deutsch
Muttersprachlich oder zweisprachig
Englisch
Muttersprachlich oder zweisprachig
Spanisch
Verhandlungssicher
Katalanisch
Verhandlungssicher

Arbeitsortpräferenzen

Vor Ort möglich

Barcelona (bis zu 50 km)

Autonomous University of Barcelona
Webscraping Specialist
FORSCHUNG
März 2024 - Heute (2 Jahre und 3 Monate)
Barcelona, Spanien
Development a script to extract both quantitative and qualitative data from over 700 EU agricultural project reports, which served as the base for policy recommendations. My tool located and pulled quantitative parameters (like location, duration, and participants) based on unique webpage characteristics, structuring the output into a CSV file. It also collected, classified, and converted relevant text passages into an open document format for further qualitative analysis.
BeautifulSoup Webscraping
Max-Planck-Institut for Interdisciplinary Natural Sciences
Image Analysis Instructor
FORSCHUNG
Mai 2023 - Juni 2023 (2 Monate)
Göttingen, Deutschland
Planning a two-day workshop on automating counting tasks in biomedical imaging for neuroscientists. I taught machine learning and thresholding based methods for automated object segmentation to PhD students, professors and other researchers. They mainly required automated pipelines to recognize nerve cells from microscopy images and extract parameters from them.
Image segmentation Image Thresholding Machine learning Convolutional Neural Networks Teaching
Wageningen University and Research
Image Analysis Specialist
FORSCHUNG
Januar 2022 - Oktober 2022 (10 Monate)
Wageningen, Niederlande
Creation of a machine learning algorithm based on the convolutional neural network Stardist to recognize and analyze chloroplasts in 3D confocal microscopy images. It involved selection and processing of a training data set, integrating and adapting the machine learning algorithm into a workflow as well as image pre- and post-processing using ImageJ and OpenCV.
OpenCV ImageJ Stardist Convolutional Neural Networks Machine learning