Research Assistants in Medical Robotics (Navigation & Control)

University of Copenhagen; København; On-site; DKK 360,000 - 480,000; Full time

Job summary

University of Copenhagen is seeking one-year Research Assistant positions in Medical Robotics to develop robot control and navigation methods for endoscope devices using simulation-based learning.

Responsibilities include ML-driven motion planning, integrating simulation frameworks, and producing impactful research outputs for journals and conferences. Applicants should have MSc in robotics/CS and strong C++/Python skills, with ROS/PyTorch experience.

Qualifications

• MSc in robotics, CS or related field.
• Strong foundation in robotics simulation, robot control, computer vision and/or ML for physical systems.
• Hands-on experience with numerical optimization applied to motion planning or reinforcement learning.
• Proficient computing with C++/Python; experience with PyTorch, ROS or similar.
• Excellent communication in a multidisciplinary, international research setting.

Responsibilities

• Design and implement ML methods for motion planning and control.
• Integrate simulation-based learning frameworks and demonstrate on real hardware.
• Publish research results in peer-reviewed outlets and present at conferences.
• Collaborate with industrial and academic partners to translate methods to clinical practice.

Skills

Robotics simulation

Machine learning

Control systems

C++/Python

ROS

Education

MSc in robotics, CS or related field

Tools

PyTorch

JAX

Warp

Taichi

ROS

MuJoCo

Isaac Sim

SOFA

Job description

Research Assistant Positions in Medical Robotics

The Department of Computer Science invites applications for one-year research assistant positions 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

• 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 positions can be extendable and towards a PhD depending on the future funding status. The project has a track record 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

Essential experience and skills

• MSc in the fields mentioned above.
• You have a strong foundation and track record in robotics simulation, robot control, computer vision and/or machine learning for physical systems.
• You are highly 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.

Tagged as: Life Sciences