Phd - Privacy-preserved Efficient Contrastive Multi-View Clustering

Applicants are invited for a PhD fellowship/scholarship at Graduate School of Technical Sciences, Aarhus University, Denmark, within the Electrical and Computer Engineering programme. The position is available from 01 July 2025 or later. You can submit your application via the link under 'how to apply'.

Title
Privacy-preserved Efficient Contrastive Multi-View Clustering

Research area and project description
This project focuses on an important research direction of multimodal learning, Multi-view Clustering (MVC), which aims to find patterns and clusters across these multi-view data to achieve a better understanding of the entity, such as classifying cancers using multi-omics data from different hospitals. Most solutions focus on centralized setups or ignore the privacy concerns of distributed setups. This project aims to enhance the privacy protection in distributed MVC without performance deterioration via incorporating techniques such as contrastive learning, to improve the intra-view consensus while introducing new distance metrics to maximize intercluster separability.

During the project, the student has opportunities and resources (such as lab and devices) to apply the developed MVC techniques to analyze multimodal biosignals collected from Virtual Reality sessions. This can significantly increase the potential impact of the developed techniques by enabling it to many interesting applications.

• Project description (½-4 pages). This document should describe your ideas and research plans for this specific project. If you wish to, you can indicate an URL where further information can be found.
  

Qualifications and specific competences
Applicants must have a relevant Master’s degree (120 ECTS), or equivalent, or receive the Master’s degree before starting. The Master’s degree shall be granted by Electrical Engineering, Computer Science, or similar departments. It is preferred that the applicants Bachelor’s degree in the above fields as well.

The project has a heavy focus on trustworthy AI, thus the background in AI especially distributed AI and/or privacy-preserved AI is preferred. The applicants should be willing to work with a wide range of experimental and theoretical topics. Experience or interest in exploring using AI in VR is a bonus. The applicants shall be able to work independently, as well as in a group.

Place of employment and place of work
The place of employment is Aarhus University, and the place of work is Finlandsgade 22, Building 5123, 8200 Aarhus N.

Contacts
Applicants seeking further information are invited to contact:

• Professor Daniel Enrique Lucani Rötter, [email protected] (main supervisor)
• Tenure Track Assistant Professor Peng Yuan Zhou, [email protected] (co-supervisor)
  

How to apply:
Please follow this link to submit your application.

Application deadline is 20 March 2025 at 23:59 CET.

Preferred starting date is 1 July 2025.

For information about application requirements and mandatory attachments, please see our application guide.

Please note:

• Only documents received prior to the application deadline will be evaluated. Thus, documents sent after deadline will not be taken into account.
• The programme committee may request further information or invite the applicant to attend an interview.
• Shortlisting will be used, which means that the evaluation committee only will evaluate the most relevant applications.
  

Aarhus University’s ambition is to be an attractive and inspiring workplace for all and to foster a culture in which each individual has opportunities to thrive, achieve and develop. We view equality and diversity as assets, and we welcome all applicants. All interested candidates are encouraged to apply, regardless of their personal background