The Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB) is a pioneer and a driver of bioeconomy research. We create the scientific foundation to transform agricultural, food, industrial and energy systems into a sustainable bio-based circular economy. We develop and integrate techniques, processes and management strategies, effectively converging technologies to intelligently crosslink highly diverse bioeconomic production systems and to control them in a knowledge-based, adaptive and largely automated manner. We conduct research in dialogue with society, policymakers, industry and other stakeholders - knowledge-driven and application-inspired. To strengthen **the Department Data Science in Bioeconomy **we are offering the following position to be filled on 1st March 2026: Scientist (m/f/d) for the Doctorate (100 %) Focus on Artificial Intelligence Extreme weather events, pests, and plant diseases increasingly threaten agricultural productivity. Farmers need precise, field-level early warning systems and practical tools for timely decision support. Current tools often rely on coarse-resolution data, limiting their usefulness for targeted decision-making. We are seeking for a highly motivated doctoral researcher to develop multi-modal AI systems that integrate different data, such as field sensors, weather data, drones (RGB, multispectral, thermal), robotic platforms (Go2 Pro EDU), and observations provided by farmers. Your work will advance pest and diseases detection, crop stress monitoring, and crop-rotation modelling, combining Physics-Aware Modelling, Explainable AI and spatiotemporal deep learning techniques. The developments should ultimately lead to usable tools for farmers, requiring a close and continuous exchange with agriculture practitioners. The position is assigned to ATB's Data Science in Bioeconomy Department, in close collaboration with the other departments.

Your tasks

• Integrate Physics-Aware Modeling and Explainable AI to ensure robustness, transparency, and agronomic interpretability,
• Build AI solutions for pest identification, disease detection, abiotic stress recognition (drought, heat, nutrient deficits), and crop-rotation interactions,
• Deploy and experimentally use drones and the robotic system (Go2 Pro EDU) as a mobile research platform for real-world data collection on fields,
• Co-design digital tools with farmers (e.g., smartphone-based diagnostics) and ensure regular field visits and user studies,
• Author scientific papers and present findings at top-tier conferences,
• Communicate and transfer project findings to project partners.

Your qualifications

• Successfully completed university degree (master, diploma, or equivalent) in computer science, physics, engineering, mathematics, or comparable field,
• In-depth theoretical knowledge in Machine Learning, especially in spatiotemporal modelling, environmental data analysis, or multimodal learning,
• Practical experience in applying Machine Learning, ideally including deep learning, foundation models, or multimodal architectures,
• Strong programming skills in Python, with experience in Machine Learning and Linear Algebra Libraries (preferably PyTorch, also JAX, TensorFlow). Experience in CUDA programming is advantageous,
• Familiarity with Git and Linux,
• Excellent written and spoken English skills, with a willingness to learn German.

Preferred qualifications

• Experience in Scientific Research,
• Familiarity with Physics-Aware Modelling and Explainable AI, and spatiotemporal forecasting methods,
• Experience working with sensor data, remote sensing, weather data, robotic platforms, or field experiments,
• Participation in academic competitions (e.g., IMO, ICPC) or high-level ML competitions (Kaggle).

We offer

• The opportunity to pursue a doctorate/PhD (Biomedical Science),
• An attractive, research-intensive, and interdisciplinary working environment,
• A varied position at the interface of science and practice,
• Excellent infrastructure for scientific work,
• Access to national and international networks for your scientific development,
• Training and further education opportunities,
• Family-friendly working conditions to promote work-life balance,
• Participation in the VBB company ticket or Deutschlandticket,
• A workplace at the edge of a picturesque landscape, easily accessible by bike or public transport.

The position ist full-time (100 %), 40 hours/week and limited to 3 years in line with the project duration. Part-time employment is also possible if desired. Remuneration is based on your qualifications and professional experience up to pay grade E 13 TV-L. For further information, please contact** Prof Dr. Marina Höhne **(E-Mail: MHoehne@atb-potsdam.de (https://mailto:MHoehne@atb-potsdam.de) ) and visit our website at www.atb-potsdam.de (http://www.atb-potsdam.de) . Have we piqued your interest? Then apply by 20th December 2025 with your cover letter, CV (without photo), and employment references and/or contact details of referees via our online application portal for this job posting (reference number 2025-DS-5) at ATB: Vacancies (https://www.atb-potsdam.de/en/career/vacancies) . Applications received after the application deadline cannot be considered. We look forward to your application! Interviews are expected to take place in the second half of January 2026. We are committed to equal opportunities. Applications from severely disabled candidates will be given preference if equally qualified. By submitting your application, you agree that your documents may be stored for up to six months even in the case of an unsuccessful application. Further information on data protection can be found here: ATB: Data Protection Declaration for the application process (https://www.atb-potsdam.de/en/data-protection-declaration-for-the-application-process) .

Bereitgestellt in Kooperation mit der Bundesagentur für Arbeit.