Scientist (m/f/d) (100%) (Data Scientist)

Fellowship details

Scientist (m/f/d) (100%) (Data Scientist)

Leibniz-Institut für Agrartechnik und Bioökonomie -
Potsdam, Deutschland, Brandenburg -
Published 28/09/2026

Company Description

The Leibniz Institute for Agricultural Engineering and Bioeconomy is a pioneer and a driver of systemic-technological bioeconomy research.
We create the scientific foundation for the transformation of agricultural, food, other industrial and energy systems into a sustainable bio-based circular economy.
We develop, deploy and integrate technologies, techniques, processes and management strategies, strategically integrate a variety of bioeconomic production systems within a comprehensive system approach and manage them in a knowledge-driven, adaptive and extensively automated way using converging technologies.
We conduct research in dialogue with society, policymakers, industry and other stakeholders – knowledge-driven and application-inspired.

Utilise proximal and remote sensing technologies to generate high-spatial-resolution soil property maps.

Deploy IoT and remote sensing technologies to establish a soil health monitoring system delivering high-temporal-resolution data streams.

Establish a federated soil data platform combining decentralised data access and governance with a secure central repository, integrating scientific data, sensor outputs and local knowledge to support soil intelligence, research and policymaking.

Develop robust AI and machine-learning algorithms for soil data fusion, predictive analytics, uncertainty quantification and scenario modelling

Co-design, adapt and integrate user-oriented decision support systems (DSS) that translate soil intelligence, predictive uncertainty and AI-driven analytics into actionable and reliable recommendations for farmers, land managers and landowners.

For further information, please contact Dr. Sebastian Vogel (E-Mail: svogel@atb-potsdam.de)

Submission of application by September 30, 2026.

Required Skills

Very good university degree (Master/Diploma) and ideally a PhD with focus in soil science and data science Very good knowledge and experience in sensor-based soil mapping and DSS; in optical spectroscopy, sensor calibration and data science. Very good programming skills (R, Python). Knowledge in agriculture, soil science, proximal and remote sensing and geographic information systems. Very good written and spoken English and good knowledge of German.