Job description

Health and nutrition sciences are undergoing radical change: artificial intelligence is fundamentally transforming the way we understand and analyze health. At Ludwig Maximilian University in Munich, we are developing AI solutions as part of interdisciplinary research projects that are having a real impact in practice—from precise nutrition tracking via smartphone to integration in clinical studies.

Our vision: to provide personalized nutrition recommendations using intelligent algorithms that are not only based on theory, but on real health data – scientifically sound, individually tailored, and technologically scalable.

Your responsibilities

• Research and teaching in the field of AI, data science, and computer vision with a focus on health and nutrition applications
• Development, training, and evaluation of AI models and prototypes—especially for mobile nutrition tracking applications
• Application and extension of methods from statistics, machine learning, and data science for complex human health issues
• Collaboration on interdisciplinary projects – from the conception phase to implementation in studies, including clinical trials
• Participation in teaching: Supervision of final theses, conducting seminars, internships, and lectures
• Support in organizing and communicating chair-internal activities, events, and collaborations

Your profile

• First-class university degree in computer science, AI, data science, or a related field
• Solid programming skills, ideally in Python
• Experience in machine learning
• Very good German skills (at least C1) and solid English skills
• Team spirit, personal responsibility, and curiosity about new technologies
• Project experience (e.g., in student teams, internships, open source, or similar) is advantageous.
• Knowledge of mobile app development (Flutter, React Native, or similar) is advantageous
• Experience working with medical or nutritional science teams is an advantage

What you can expect

• Exciting, interdisciplinary research with direct practical application
• Practical relevance: We don't just think about AI in theory, we put it into practice – including studies with real users.
• Team spirit: collegial, motivated environment with a high degree of personal responsibility
• Modern technologies & access to real data from health research
• Development prospects: Publications, conference attendance, career development in an academic context
  

Contact

We look forward to receiving your detailed application, including a cover letter, resume, and references. Please send these preferably in a single PDF document (max. 5 MB) by email to: jobs@mobile.ifi.lmu.de . The application period is open immediately and will remain open until the positions are filled.