Two Student Research Assistants (m/f/d) (40-80h per month) Focus on Artificial Intelligence

Overview

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 looking for two Student Research Assistants (m/f/d) (40-80 hours per month) focusing on Artificial Intelligence. Core research themes include applied machine learning methods for real-world systems. Possible research directions include:

• Transfer learning and domain adaptation across heterogeneous production environments (e.g., food processing, bioconversion and fermentation processes)
• Self-supervised learning for multimodal sensor data (e.g., spectroscopy, hyperspectral imaging, 3D point clouds, and other high-dimensional data)
• Time series modeling, forecasting, and real-time monitoring in dynamic bioeconomic systems
• Data-driven modeling and intelligent control in bioeconomic systems
• Out-of-distribution (OOD) generalization in process monitoring and control
• Explainable Artificial Intelligence (XAI) for interpretable decision-making in biosystems

Responsibilities

• Collaborate with researchers to design, develop, and evaluate advanced AI models
• Assist in experimental design, data annotation, data preprocessing, and evaluation
• Implement and test AI models using real-world data
• Contribute to scientific publications, reports, and presentations
• Participate actively in team meetings and research discussions

Qualifications

• Currently enrolled in Computer Science, Data Science, Mathematics, or a related field
• Basic knowledge in machine learning and deep learning
• Excellent programming skills in Python
• Practical experience with PyTorch (preferred) and/or with TensorFlow, scikit-learn, and GitHub
• Experience with scientific experimentation and reproducible research practices is a plus
• Very good written and spoken English skills
• Independent, structured working style and strong analytical thinking
• Knowledge of time series analysis, domain adaptation, or bioeconomic systems is a plus but not required

We offer

• Participation in cutting-edge research on AI
• Opportunity to contribute to scientific publications and open-source frameworks
• Supervision by experienced scientists
• An attractive, research-intensive, and interdisciplinary working environment
• A highly motivated, international team
• Excellent infrastructure for scientific work
• Flexible working hours and excellent equipment
• Family-friendly and flexible working hours and excellent equipment
• A workplace at the edge of a picturesque landscape, easily accessible by bike or public transport

Application details

The position is to be filled with 40 to 80 hours per month and is limited to one year. The salary is dependent on your degree (14.59 Euros per hour with Bachelor’s degree, 13.98 Euros per hour without degree).

For further information, please contact Prof. Dr. Marina Höhne (E-Mail: ) and visit our website at .

Please apply online by 12 April 2026, including a strong motivation letter demonstrating your suitability for the advertised student research assistant position, a detailed CV, all certificates with grades (A levels and the current transcript of Bachelor and/or Master courses and grades), and any recommendation letters via our application portal (reference number 2026-DS-1). Applications received after the application deadline cannot be considered.

The interviews will take place from 20 to 24 April 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.