The posting
The Department of Computer Science invites applications for one-year position focused on developing innovative robot control and navigation techniques using simulation-based learning for medical robotic endoscope devices.
Project Background This project addresses two critical challenges in the field of medical robotics to improve patient care through advanced simulation and control:
- Image-Based Navigation: Creating reward functions for scoring navigation policies for medical robotic devices moving inside the human body, relying solely on image information and accounting for environment changes through interaction models.
- Soft Robot Control: Developing learning-based methods to control a soft robot endoscope via high-level navigation policies to perform clinical procedures inside the human body, including quality assessment of these methods during in-vivo interventions.
The successful candidates will join a multidisciplinary and collaborative team renowned for cutting-edge research in medical imaging and simulation technologies, operating within a global network across France, Germany, and Spain.
Roles and Responsibilities The successful candidates will play a central role in the project’s technical and scientific success. While the level of autonomy will vary by position, both roles will share the following core responsibilities:
- Technical Development & Implementation: Designing and implementing machine learning methods for motion planning and control. This includes integrating simulation-based learning frameworks and demonstrating the resulting systems on real robotic hardware and soft robot endoscopes.
- Research & Scientific Contribution: Contributing to the project’s core objectives by producing impactful research outputs. This includes writing high-quality papers for peer-reviewed journals and presenting findings at international conferences.
- Collaboration & Knowledge Exchange: Facilitating collaborations with industrial partners and academic collaborators to ensure that the developed methodologies are meaningful and translatable to real-world clinical practice.
- Professional Growth & Mentorship: Engaging in a high-growth research environment. The position is extendable depending on the future funding status. The project has a trackrecord of landing members in top PhD program and faculty positions.
- Interdisciplinary Integration: Actively participating in team discussions and workshops to integrate expertise across medical imaging, physics simulation, and robotics control.
Profile We are looking for a highly motivated and enthusiastic scientist with the following competencies and experience:
Essential experience and skills
- You have a PhD in Computer Science, Robotics, Biomedical Engineering, Mechanical/Electronic Engineering, Applied Math, or a related field.
- You have a strong foundation and track record in robotics simulation, robot control, computer vision and/or machine learning for physical systems.
- You are highgly experienced in numerical optimization algorithms, preferably applied to motion planning or reinforcement learning. Hands-on experience on real robots especially soft robot systems is a plus.
- Proficient scientific computing and programming (C++/Python) and experience with libraries such as PyTorch, JAX, Warp, Taichi, or ROS.
- Excellent communication skills and a high level of motivation to work in a multidisciplinary, international research environment.
Desireable experience and skills
- Experience in publishing peer-reviewed research in top-tier robotics or AI venues.
- Familiarity with physics simulation such as MuJoCo, Isaac Sim, Newton Physics, SOFA etc.
Terms of employment The average weekly working hours are 37 hours per week.
The position is a fixed-term position limited to a period of 1 year. The starting date is 15 February or after agreement
Salary, pension and other conditions of employment are set in accordance with the Agreement between the Ministry of Taxation and AC (Danish Confederation of Professional Associations) or other relevant organisation.
Foreign and Danish applicants may be eligible for tax reductions, if they hold a PhD degree and have not lived in Denmark the last 10 years.
The position is covered by the Job Structure for Academic Staff at Universities 2025.
Questions Further information on the Department is linked at http://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the positions can be made to [email protected] and [email protected].
Application procedure
- Your online application must be submitted in English by clicking ‘Apply now’ below. Furthermore, your application must include the following documents/attachments – all in PDF format
- Motivated letter of application (max. one page).
- CV incl. education, work/research experience, language skills and other skills relevant for the position.
- A certified/signed copy of a) PhD certificate and b) Master of Science certificate. If the PhD is not completed, a written statement from the supervisor will do.
- List of publications.
Deadline for applications: 30 November 2026, 23:59 GMT +1. We reserve the right not to consider material received after the deadline, and not to consider applications that do not live up to the abovementioned requirements.
The further process After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the hiring committee. All applicants are then immediately notified whether their application has been passed for assessment by an unbiased assessor. Once the assessment work has been completed each applicant has the opportunity to comment on the part of the assessment that relates to the applicant him/herself.
You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/
The applicant will be assessed according to the Ministerial Order no. 242 of 13 March 2012 on the Appointment of Academic Staff at Universities.
The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.
