If you’re the kind of person who sees messy spreadsheets full of raw data and thinks,
“There’s a better way to do this…” then this project might be for you!
Background
Every week, thousands of data points are generated across small-scale screenings and bioreactor fermentations.
But too often, this valuable data lives in silos, scattered across Excel sheets, systems, and ELNs, making it difficult to compare, learn, and optimize across scales.
The goal of this project is to design and implement a streamlined data management framework that transforms unstructured fermentation data into actionable insights.
You’ll be at the intersection of bioprocess engineering, data science, and digital innovation, shaping how fermentation data is captured, structured, visualized and correlates to small scale screening.
Project Objectives
By The End Of This Project, You Will
- Map the data landscape: Identify all sources of data (small-scale, bioreactor, analytical) and understand how data flows between systems.
- Design a unified data structure: Create a standardized data system linking small-scale screening with bioreactor results.
- Build an automated data pipeline: Using Python, Power Automate or other automate data transfer and cleaning to reduce manual work.
- Develop correlation and insight dashboards: Visualize patterns between scales (e.g., small-scale vs. bioreactor titer, yield, and growth rate correlations).
- Propose an implementation roadmap: Deliver a strategy on how to scale the solution across future projects and teams.
Who We’re Looking For
Curious by nature: you ask why until things make sense.
Learns at lightning speed: you don’t wait to be told; you dive in, test, and adapt.
Creative problem solver: when data gets messy, you see patterns where others see chaos.
Positive energy: you bring good vibes, initiative, and the kind of attitude that makes everyone better around you.
If that sounds like you...you’ll thrive here.
Because this isn’t a project where you just follow instructions.
It’s a chance to build something that changes how fermentation data is handled forever.
Ideal Profile
- Master’s student in Bioinformatics, Data Science, or Biotechnology.
- Experience (or interest) in fermentation and microbial processes.
- Comfortable with Python, statistical tools (or excited to learn).
- Thrives in cross-functional collaboration.
If that sounds like you, don’t wait.
Send your CV and a short motivation on why you want to build this.
Questions about the project? Contact Periklis Sotiris - ps@biosyntia.com
