PhD Positions within Robot Imitation Learning and Biomedical Sensing

SDU Robotics invites applications for one or more fully funded PhD position(s), where the candidates will work within the area of robot imitation learning and control and biomedical sensing technology. The positions are for a 3-year period. The starting date is 1 September 2024 or as soon as possible thereafter and will be agreed with the successful candidate.  

The application deadline is 6 May 2024 at 23.59 (CET/CEST) 

Research environment 

The candidates will be integrated in the section SDU Robotics, which is a team of approx. 50 employees, specialized in research and development of robot solutions within the medical, welfare and industrial domain. We value teamwork, professional diligence, enthusiasm for robotics and the drive to adopt new skills and extended responsibilities. We offer an open, international team with flexible work organization and support of individual development.

SDU Robotics is involved in a variety of national and European projects and features a strong network of academic and industrial partners. The aim of the group is to solve challenging research problems derived from real-life challenges by implementing novel robot solutions. We participate in implementing the achieved results in real solutions with end users as national hospitals, Universal Robots, LEGO and Novo Nordisk.

SDU Robotics is part of the Maersk Mc-Kinney Moller Institute, University of Southern Denmark (SDU), and located at the main Campus in Odense, at the core of the Odense Robotics Cluster involving 130+ startups and established companies in robotics. 

Project description 

In the motivation letter, the candidates are requested to state which of the two positions is preferred.

Project 1 – Data-Efficiency and Safety Guarantees in Robot Imitation Learning

This project will investigate methods for data efficiency and for guaranteeing the convergence and safety of robot imitation learning. The methods will be applied to various use cases, ranging from learning autonomous surgical procedures such as suturing using visuomotor behavioral cloning, to learning control and manipulation for disassembly. A focus of the project will be on transfer learning and cross-domain learning, as well as on bridging the gap between behavioral cloning using neural networks for long-horizon planning and movement-primitive-based controllers for short-horizon adaptation.

In addition to the qualifications mentioned below, it is preferred that the candidate have knowledge of some of:

• Control theoretic methods for safety and convergence guarantees.
• Visuomotor behavioral cloning (e.g., implicit behavioral cloning, behavioral transformers, diffusion policies, etc.).

Project 2 – Biomedical sensor and AI algorithm for laryngeal cancer diagnosis

This project aims to develop a reliable and miniaturized bio-sensor probe for laryngeal cancer on-site diagnosis. The PhD candidate will be responsible to:

• Simulate and optimize electrodes’ configuration for improving Electrical Bio-Impedance sensing reliability.
• Analysis clinical data from hospital partners using medical statistical tools.
• Develop AI algorithms to improve cancer detection accuracy.

Profile and requirements 

The candidates will participate in SDU Robotics’ comprehensive research and teaching activities within the areas of medical and surgical robotics, industrial (dis)assembly and (re)manufacturing, artificial intelligence, control, AI algorithms and biomedical sensing techniques. The positions require a master’s degree within robotics, electrical engineering, welfare technology, machine learning, or a similar/relevant area. The candidates are expected to have a profound knowledge on the majority of the following topics:

• Robotics (e.g., modelling, kinematics, dynamics, and control).
• Programming skills (particularly in C++, Python and ROS).
• Artificial Intelligence and Machine Learning.
• COMSOL simulation.
• Experiment design and data analysis.

Furthermore, the successful candidates are expected to:

• Have excellent knowledge of English (written and spoken).
• Be able to work well and communicate expert knowledge in an interdisciplinary team.
• Have high self-motivation to learn. 
• Have the ability of working independently. 
• Have a strong sense of responsibility.

Further information

Please visit us on LinkedIn: https://www.linkedin.com/company/sdu-robotics. 

Further information about this position is available via e-mail from Iñigo Iturrate (injummmi.sdu.dk) for Project 1 and Zhuoqi Cheng (zchmmmi.sdu.dk) for Project 2. 

If you experience technical problems, you must contact hcm-supportsdu.dk.

Further information for international applicants about entering and working in Denmark.

Further information about The Faculty of Engineering.

Application procedure

Before applying the candidates are expected to read the Faculty information for prospective PhD students, SDU information on How to apply, and Faculty information on How to apply – Academic staff.

The application must be in English and must include:

• A motivation letter that clearly explains the applicant's interest, qualifications, and motivation for the position (max. 2 pages) – remember to state which of the two positions is preferred.
• Detailed Curriculum Vitae including personal contact information.
• Verified copies of the official bachelor diploma and master's diploma and transcripts of exams, both the original documents and in professional English translation.
• Completed TEK PhD application form for 5+3 applicants. Find the form at the Faculty website.
• Completed TEK PhD form for calculation grade point average. Find the form at the Faculty website. 
• An official document describing the grading scheme of the awarding universities (if not Danish). 
• For applicants from programmes that evaluate thesis/examination project by approved/not approved: Please submit an official and verified written assessment of the thesis or dissertation project from the grade giving institution. The statement must clearly state that the candidate has been among the top 30 pct. in the graduation class for the study programme.

The application may also include:

• References (names and emails) and/or Reference letters, you're welcome to use the form for reference letter at the Faculty website.
• List of publications and maximum 2 examples of relevant publications (in case you have any publications).

Applications received after the deadline or outside the official recruitment portal will neither be considered nor evaluated.

Assessment and selection process

Applications will be assessed by an assessment committee or an expert. Shortlisting may be used. Only shortlisted candidates will be assessed. Applicants will be informed of their assessment by the faculty. Interviews and tests may be part of the selection process.   

Conditions of employment

Applicants must hold a master’s degree (equivalent to a Danish master's degree) at the time of enrollment and employment. 

Employment of a PhD fellow can only happen after the PhD School has approved the candidate for admission. Employment and enrollment will cease without further notice at the end of the period. A PhD fellow is not allowed to have any kind of sideline employment, while enrolled as PhD fellow at the faculty.

Employment as a PhD fellow is a 3-year salaried position and is governed by the Protocol on PhD Research Fellows signed by the Danish Ministry of Finance and the Danish Confederation of Professional Associations. Further information about salary and conditions of employment. 

The successful candidate will be enrolled at SDU in accordance with Faculty regulations and the Danish Ministerial Order on the PhD Programme at the Universities (PhD order).

The application deadline is 6 May 2024 at 23.59 (CET/CEST) 

Formalities

• All files must be in English.
• Documents should not contain a CPR number (civil registration number) – in this case, the CPR number must be crossed out.
• The application and CV must not exceed 10 MB. 

The University of Southern Denmark wishes to reflect the surrounding community and therefore encourages everyone, regardless of personal background, to apply for the position.