Scientific Employee/PhD Student (f/m/d)

The University Medical Center Göttingen (UMG) unites the Medical Faculty of the Georg-August University and the University Hospital in an integration model. With around 9,700 employees, the UMG and its subsidiaries are one of the largest employers in the region. Our clinics and institutes stand for high-quality patient care, excellent research, modern teaching and transfer of innovative technology.

Göttingen as a city of science is located in the center of Germany and the University Medical Center Göttingen is integrated into an attractive network of university and non-university scientific institutions.

The Klinik für Allgemein-, Viszeral- und Kinderchirurgie of the University Medical Center Göttingen is looking for a new position for the earliest start date

Scientific Employee/PhD Student (f/m/d)

part time, 19,25 hours per week, initially limited to 31.05.2029

Remuneration according to TV-L

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

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

Your qualifications

Masters 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

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