- Biostat, Obesity & Liver Diseases- Clinical trials- Research & Development

• Assistant statistician at Department of Plant and Environmental Sciences• Developing computational methods for dose-response models• Analyzing drone data to identify underlying field trends in selective breeding• Research on dose-response models• Mainly R programming and reading scientific articles in the field• Goal is a publishable manuscript with an R package

A full-time summer internship with additional part-time stay during part of the winter semester. Part of AI/ML team developing a next-gen solution for criminality detection on financial transactions.• Techniques: - Times Series modeling and anomaly detection - Model selection and validation - Object-oriented programming in the context of a complex project - Presenting results in an interactive dashboard• Technologies and development: - Python (NumPy, Pandas, Scikit-learn, Pytest, Dash, Plotly, ...) with PyCharm and Jupyter - Git - Agile development

Summer intern - writing basic SQL queries for data warehousing.