Data Scientist (f/m/d)

Universitätsmedizin Göttingen I UMG; Göttingen; Vor Ort; EUR 60.000 - 80.000; Vollzeit

Zusammenfassung

The Center for Digital Surgery at Universitätsmedizin Göttingen invites applications for a research position focused on Surgical AI and Robotics. We bridge methodological research with clinical application using multimodal data, intra-operative and pre-operative imaging, biosignals, and EHRs to build intelligent surgical assistance systems.

Key responsibilities include developing real-time image analysis pipelines, evaluating deep learning architectures for surgical video analysis, and

Qualifikationen

• Master’s degree required in a relevant field.
• Strong motivation for research and innovation.
• Ability to learn and grow in an interdisciplinary team.
• Organizational and team skills, flexibility and open-mindedness.
• Very good Python programming skills; experience with ML/DL is a plus.

Aufgaben

• Perform applied research in intra-operative assistance systems using laparoscopic video streams.
• Design, implement and test image analysis pipelines for anatomical landmark recognition.
• Research DL architectures for object detection/segmentation in surgical videos.
• Develop and validate concepts for an assistance system with clinical value, in collaboration with clinicians.
• Collaborate with industrial partners to translate findings toward a product.
• Co-supervise student researchers.

Kenntnisse

Programming

Python

Machine learning

Deep learning

Team collaboration

Communication skills

Ausbildung

Master’s degree in biomedical engineering, data science, computer science or similar field of study

Tools

Python

Jobbeschreibung

The Center for Digital Surgery is a research hub on Surgical AI and Robotics, with a strong focus on bridging the gap between methodical research and its clinical application.

The research group of Prof. Dr. Hagenah aims at „making surgery intelligent“ by leveraging multimodal data, e.g. intra-operative as well as pre-operative images, biosignals and electronic health records, to build AI-driven and robotic surgical assistance systems. Since the Center for Digital Surgery is part of the Department for General, Visceral and Pediatric Surgery and closely related to the Göttingen School of Surgery, we are working on closing the loop from clinical data collection over methodological research and proof‑of‑concept‑studies in lab setups to the application of clinical demonstrators in the operating room.

• Perform applied research in the field of intra-operative assistance systems utilizing laparoscopic video streams
• Design, implement and test image analysis pipelines for anatomical landmark recognition
• Perform research on efficient and effective deep learning architectures for object detection or segmentation in surgical videos
• Develop and validate concepts for an assistance system with real clinical value in close collaboration with clinical experts
• Collaborate closely with industrial partners to translate your findings towards a product
• Co-supervise student researchers

• Master’s degree in biomedical engineering, data science, computer science or similar field of study
• High intrinsic motivation with a passion for research and innovation
• Ability to continuously learn and grow within an interdisciplinary team
• Organizational and team skills, flexibility, open-mindedness and communication skills
• Very good programming skills, preferably experience with machine learning/deep learning using Python
• Experience in one or more of the following fields is a plus:

Medical Image Analysis Deep Learning, with special emphasis on video analysis R&D in industry

• A challenging workplace full of opportunities in a multi-disciplinary, cooperative team
• The unique opportunity to translate your technical research to the clinical application with minimal obstacles
• A lot of room for creative freedom and shaping your optimal work environment together
• State-of-the-art equipment
• Support of personal advancement via intensive mentoring, promotion of networking, and mental as well as practical support in research activities through a team-oriented mindset

Wir freuen uns auf Ihre Bewerbung!