Einstein Foundation Early Career Award 2025

Erring Rigorously

“Erring Rigorously sharpens the line between real biological signals and technical noise – boosting data reliability in line with the Early Career Award’s goals and the Berlin Institute of Health’s commitment to patient-centered, reproducible, transparent science.”

Christopher Baum, Chair of the Board of Directors of the Berlin Institute of Health at Charité, which funds the Early Career Award

Portrait of Maximilian Sprang
Maximilian Sprang, Lead Researcher of Erring Rigorously

The project Erring Rigorously aims to explore how mistakes and differences in laboratory experiments can affect the reliability of scientific results. By deliberately introducing controlled errors in sequencing experiments, the project measures their impact using an advanced machine learning tool that predicts data quality. Building on previous work in functional genomics, the project connects lab experiments with computational analysis to make scientific findings more reproducible and easier to interpret in real-world research. The project led by Maximilian Sprang, Junior Group Leader at the University Medical Center of the Johannes Gutenberg University Mainz, is awarded €100,000.

→ Watch a short interview with Early Career Award Winner Maximilian Sprang, Lead Researcher of Erring Rigorously, interviewed by Award Secretary Ulrich Dirnagl

The Signal and the Noise

Enhancing Research Reliability – the Early Career Award winners explore how experimental errors shape genomic data, developing tools to make analyses more accurate and reproducible. 
 

Even the most advanced biomedical experiments can be disrupted by small mistakes, creating misleading results that look like real biological signals. Erring Rigorously, led by bioinformatician Maximilian Sprang, is a pioneering project awarded the €100,000 Einstein Foundation Early Career Award, funded by the BIH QUEST Center for Responsible Research, which will systematically explore how errors in sequencing experiments influence the conclusions scientists draw. 


The jury praised the project, selected from more than 70 global applications for tackling a fundamental challenge in functional genomics and its potential to set new standards for integrating experimental and computational research.


“Maximilian Sprang’s project Erring Rigorously explores how to separate true scientific signals from noise and technical errors, strengthening the reliability and reproducibility of research.” (Marcia McNutt, president of the U.S. National Academy of Sciences and president of the award jury) 
 

Sprang earned his PhD in Bioinformatics from Johannes Gutenberg University Mainz in October 2024, summa cum laude, where he introduced the concept of Quality Imbalance, showing that differences in data quality between biological groups can distort results in over 30% of public RNA-seq datasets, including clinically relevant studies. Since March 2025, he leads a junior research group at the Medical Center of Mainz, combining bioinformatics and AI to uncover patterns in biological data and aid translational research in immunology. 


Sprang emphasizes that ‘bad data’ should not automatically be discarded, as even low-quality samples can yield meaningful biological insights when their biases are understood. By combining controlled wet lab perturbations with machine-learning quality assessment, Erring Rigorously will generate openly accessible datasets and analytical tools to strengthen reproducibility, transparency, and reliability in functional genomics.

→ all winners and finalists