Junior Software Engineering (Bio-IT)

Our client is a Swiss Bio-IT consultancy that does modelling and simulation for the biotech and pharma industry. They’re looking for a technically strong student to build a standalone simulation interface for a PK/PD (pharmacokinetic/pharmacodynamic) model. You’ll take the existing model code, turn it into a fast data pipeline, and build an interactive app on top of it. The app will be packaged so that a Swiss biotech end client can run it on their own. The internship starts as soon as possible and runs for 1-2 months. You’ll work closely with the client’s modelling team and deliver documented, maintainable software for a real use in drug development.

Your Tasks

• Translate and implement the existing PK/PD model in R (e.g. moving simulx code to mrgsolve, rxode2 or deSolve)
• Run ODE-based simulations and generate structured simulation datasets
• Design an efficient storage layer (Apache Parquet or SQLite) so the interface reads data quickly
• Create responsive, clinical-grade charts such as concentration-time curves and dose-response plots
• Make sure the R outputs and the Python inputs fit together seamlessly, and debug any issues between the two languages
• Package the application as a standalone executable (e.g. with PyInstaller or cx_Freeze) with clean dependency management
• Write clear user manuals and code documentation so the end client can run the tool and the team can maintain it after you leave

Requirements

• You’re studying for a Master’s (or are at an advanced Bachelor’s stage) in Bioinformatics, Computational Biology, Data Science, Software Engineering or a related field
• Strong R skills, including data manipulation (tidyverse, dplyr)
• A solid understanding of ordinary differential equations (ODEs) and basic numerical simulation
• Strong Python and pandas skills for loading and filtering data
• Hands-on experience building interactive apps or dashboards with Streamlit or Plotly Dash
• Confidence with visualisation libraries such as Plotly or Altair
• An understanding of flat-file vs. columnar data structures, and experience with Parquet or SQLite
• Experience with environment management (Conda, pip or Poetry) and Git
• A basic understanding of freezing Python apps into executables, or the motivation to learn it quickly
• Nice to have: prior exposure to PK/PD concepts and experience with mrgsolve, rxode2 or deSolve

Benefits

• Start: As soon as possible
• Duration: 1-2 months
• Location: Basel office, with home office possible for independent tasks
• Workload: 80-100%
• Hourly wage: Competitive