Postdoc in Simulation-based Adaptation for Robotic Data Reuse

Department of Computer Science
Faculty of Science
University of Copenhagen
The Department of Computer Science invites applications for a two-year postdoctoral position with possibility for further extension. The successful candidate will engage in developing novel robot automation and adaptation techniques using simulation and machine learning methods. This unique opportunity focuses on two key challenges. The first is to create algorithms that can process previous manufacturing data of various formats and transfer the robot motion to fit the new task requirements and setup. The second significant challenge is using simulation to synthesize task data, and accordingly validate and refine the robot motion with model-based learning/optimization. The role demands a strong foundation in robot learning and control, and a keen interest in applying simulation-based machine learning techniques to solve these complex and practice-oriented challenges in digital manufacturing.

The successful candidate for this postdoctoral position will be joining a multidisciplinary and collaborative team at Department of Computer Science, renowned for its cutting-edge research in image analysis and simulation technologies. This team is comprised of experts in various fields, creating a rich environment for innovation and interdisciplinary learning. The team operates in a highly collaborative environment, encouraging the exchange of ideas and expertise. Regular meetings and workshops are conducted to discuss progress, challenges, and strategies, ensuring a cohesive and focused approach to the project goals. Senior members of the team, including leading researchers and professors, provide mentorship and guidance. They are committed to nurturing the next generation of scientists, offering support in both research and career development. The project is part of a consortium, networking academic researchers and industrial professionals both within and outside Denmark. The other partners include world-class tech leaders on the frontiers of collaborative robots, biomedical manufacturing and automation solution, who will be sharing best practices and staying abreast of the latest developments in the scope of the project. The team is driven by a shared goal to make significant contributions to the field of data-driven robotics and smart manufacturing. There is a strong emphasis on creating practical, innovative solutions that can be translated into real-world applications.

The candidate will be expected to contribute significantly to the research objectives, demonstrating both technical expertise and collaborative skills. Key performance expectations include:

Research at the Core
The ultimate goal is to make a significant contribution to the field of practical robot learning and smart engineering. This includes producing impactful research outputs, such as publications in high-quality venues, and potentially developing technologies or methodologies that can be applied in real-world settings.

Career Growth
While contributing to the project, the candidate is also expected to focus on their professional growth, taking advantage of mentorship opportunities, networking, and other resources provided by the institution.

Collaboration is Central
Given the interdisciplinary nature of the team, the candidate must excel in collaborative environments. This includes actively participating in team discussions, sharing knowledge and expertise, and contributing to a positive and productive team dynamic.

Communication in Focus
The candidate must be able to clearly and effectively present research findings to both technical and non-technical audiences, including writing high-quality research papers and presenting at conferences.

Qualifications:

• PhD in a relevant field such as Computer Science, Mechanical/Electronic/Automation Engineering, Applied Mathematics/Physics with a specialty in Artificial Intelligence/Robotics.
• Strong foundation in robotics, machine learning, and/or dynamic simulation.
• Experience on machine learning and robotic systems in particularly manipulation; The candidate is expected to publish on ICRA/IROS or other similar venues. A trackrecord on relevant topics such as imitation learning, transfer learning, sim2real reinforcement learning, motion planning and control etc. will be a plus.
• Proficiency in C++/python or other programming languages for building and maintaining software packages. Familiarity to robotics simulators such as Issac Sim/MuJoCo etc.

The postdoc’s duties will include research within computer science as well as teaching. The post may also include performance of other duties.

Further information on the Department is linked at https://www.science.ku.dk/english/about-the-faculty/organisation/. Inquiries about the position can be made to [email protected] and [email protected].

The position is open from 1 October 2024 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment
The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include:

• Curriculum vitae
• Diplomas (Master, Bachelor and PhD degree or equivalent)
• Research plan – description of current and future research plans
• Complete publication list
• Separate reprints of 3 particularly relevant papers

The deadline for applications is 1 August 2024, 23:59 CEST.

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at https://employment.ku.dk/faculty/recruitment-process/.

Københavns Universitet giver sine knap 10.000 medarbejdere muligheder for at udnytte deres talent fuldt ud i et ambitiøst, uformelt miljø. Vi sikrer traditionsrige og moderne rammer om uddannelser og fri forskning på højt internationalt niveau. Vi søger svar og løsninger på fælles problemer og gør ny viden tilgængelig og nyttig for andre.

Info
Ansøgningsfrist: 01-08-2024

Ansættelsesdato: 01-10-2024

Arbejdstid: Fuldtid

Afdeling/Sted: Department of Computer Science