Scientific Employee/PhD Student (f/m/d) (Ingenieur/in - Medizintechnik)

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.

Your tasks

- Perform research in the field of closed-loop medication systems, aiming at point-of-care antibiotics level measurement from whole blood and utilizing this data for automated dose control
- Design, implement, test and validate machine learning approaches to analyze data from novel sensors and fuse it with multimodal clinical data
- Collaborate closely with clinical experts at the intensive care unit, including data collection and tests in the real ward
- Present and publish your research at national and international level
- Co-supervise student researchers
- Participate in teaching activities

Your qualifications

- 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:
Analysis of clinical time series and electronic health records (EHR)
Biomedical sensing and biosignal analysis
Closed-Loop-Systems and control, preferably in medical applications

We offer

- 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

Ergänzende Informationen:
Anforderungen an den Bewerber:
Grundkenntnisse: Machine Learning, Elektronische Patientenakte - ePA, Programmiersprache Python