16 computer-science-image-processing Postdoctoral positions at Technical University of Munich
Sort by
Refine Your Search
- 
                Listed
- 
                Category
- 
                Field
- 
                
                
                advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher 
- 
                
                
                programming for workflow automation and data handling Familiarity with high-content imaging and quantitative analysis is a plus Interest in interdisciplinary approaches at the interface of biology, technology 
- 
                
                
                of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine. We work at the intersection of artificial intelligence, medical imaging, and clinical practice, developing methods 
- 
                
                
                often represented in large neural networks that are hard to analyze and whose decision processes cannot be interpreted by humans. To make this technology available without sacrificing safety concerns, we 
- 
                
                
                : Excellent Master’s degree (or equivalent) in computer science, engineering, or related disciplines (typically mathematics, physics). For Postdoc applicants: Excellent track record in computer science 
- 
                
                
                efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes the evaluation 
- 
                
                
                motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service 
- 
                
                
                -)Statistics, (Bio-)Informatics, Computer Science or related disciplines Strong background in modeling multi-modal data (images, tables, text, etc) Understanding of biases and causal inference Experience with 
- 
                
                
                energy efficiency while keeping the grid reliable and secure. Our research method is engineering-oriented, prototype-driven, and highly interdisciplinary. Our typical research process includes 
- 
                
                
                . Your qualifications An excellent PhD degree either in Computer Science, Physics, Mathematics or related fields, ideally with a background in quantum theory, quantum computing or quantum machine learning