Profile
- Department/Institute:
- Institut für Schlaganfall- und Demenzforschung (ISD)
- Subject area:
- Artificial intelligence, deep learning, image analysis, bioinformatics
- Name of supervisor:
- Ali Ertürk
- Number of open positions:
- 2
- Project title:
- AI models for 3D image data analysis
- Project time plan
- Full Doctoral Study-Model: 48 months
- Language requirements:
- English at least B2 (TOEFL score >80, >25 in the Speaking Section preferred)
- Academic requirements:
- • Undergraduate degree in computer science or related field.
• Experience in AI-based image analysis or related fields preferred.
Unfortunately, for administrative reasons we cannot accept students from the following institutions:
• Beihang University (Beijing University of Aeronautics and Astronautics), Beijing
• Beijing Institute of Technology, Beijing
• Harbin Engineering University, Harbin
• Harbin Institute of Technology, Harbin
• Nanjing University of Aeronautics and Astronautics, Nanjing
• Nanjing University of Science and Technology, Nanjing
• Northwestern Polytechnical University, Xi'an
Project description:
Our group's main objective is to accelerate biomedical research through innovative integration of cutting-edge technologies (e.g., see Pan...Ertürk, Cell, 2019; Zhao...Ertürk, Cell, 2020; Bhatia...Ertürk, Cell, 2022; Mai...Ertürk,Nature Biotechnology, 2024, Kaltenecker...Ertürk, Nature Methods, 2024). We uniquely combine whole-body clearing and three-dimensional imaging techniques for whole mice and large human tissues with artificial intelligence (AI). Our research interests encompass mapping systemic health and disease processes throughout the body, conducting molecular analyses of spatially defined physiological and pathophysiological structures, developing novel drug delivery approaches, and creating new AI and experimental technologies to enhance our comprehension of mammalian physiology. For the current project, we are seeking two skilled computer/data scientists to help with the development of generalizable models for 3D microscopic image analysis. Current methods require extensive manually annotated data, which is labor-intensive, costly, and scales poorly - especially for 3D images. Our goal is to develop generalizable approaches that can handle diverse analysis tasks using cutting-edge machine learning techniques trained on diverse in-house and external microscopy datasets. Proficiency in programming environments such as Python or R, and in data visualization approaches will be essential. Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow) an advantage. The project seamlessly bridges AI, high-performance computing, and bioinformatics to transform high resolution imaging data into biological insights.
To applicants: Please send following initial application documents to LMU-CSCOffice before December 15th:
- Resume and Research Motivation Letter
- Certificate of Proficiency in English, equivalent to IELTS Test Academic 6.5 (no module below 6) or TOEFL IBT 95, is required
- Two letters of recommendation directly sent from your current Supervisors/Professors to LMU-CSC Office
Contact LMU-CSC Office: csc.international@lmu.de