Daniel Loos

Dr. Daniel Loos is a Data Scientist and PostDoc at the Max Planck Institute for Biogeochemistry in Jena, Germany. His work focuses on leveraging Earth's spherical properties in deep learning models for the Open-Earth-Monitor Cyberinfrastructure project and developing deforestation detection workflows for the ESA’s FAIRSenDD project. He is affiliated with the Biogeochemical Integration Department and contributes to the Ecosystem Function from Earth Observation and Global Diagnostic Models research groups.

Dr. Loos’s research interests span Earth observation, bioinformatics, and computational biology. His work integrates environmental data with advanced machine learning techniques to address ecological challenges, including deforestation monitoring and microbiome analysis.

Scientific publications highlight his contributions to fungal metagenomics, gut microbiota dynamics under antibiotic exposure, and software development for microbiome data analysis. His recent work explores microbial interactions across host, aquatic, and soil ecosystems, emphasizing computational modeling and environmental genomics.

While no scientific awards are mentioned, Dr. Loos’s expertise in Julia programming and environmental data science underscores his role in advancing cyberinfrastructure for ecological monitoring. His academic and professional trajectory includes a PhD in Bioinformatics from the Leibniz Institute for Natural Product Research and Infection Biology (2018–2023), a Master’s in Bioinformatics from Friedrich Schiller University Jena (2015–2017), and a Bachelor’s in Molecular Life Science from the University of Lübeck (2012–2015).