Post doctor (2 years) within privacy for manifold data and high-dimensional data - ,

To our institution, which conducts research at the highest international level and offers several high-quality educational programs, we are now seeking a postdoctoral researcher to work on privacy for manifold data and high-dimensional data. The position is full-time for two years, starting on 1st July, or as agreed upon.

The Department of Computing Science has been growing rapidly in recent years, with a focus on creating an inclusive and bottom-up driven research environment.  Our workplace consists of a diverse set of people from different nationalities, backgrounds and fields. As a postdoctoral researcher working with us, you receive the benefits of support in career development, networking, administrative and technical support functions, along with good employment conditions. More information about the department is available at: https://www.umu.se/en/department-of-computing-science/

Project description and working tasks

The project will develop privacy-aware machine learning (ML) models. We are interested in models for complex data, including manifold and high-dimensional data, and language models. We are interested in both data-driven models as well as models built from synthetic data. Within privacy, we are interested in different types of privacy measures and models (differential and integral privacy, k-anonymity), different scenarios (centralized and decentralized data; local and global privacy). For decentralized data, we consider federated learning.

The Privacy-aware transparency decisions research group (led by Prof. Vicenç Torra) conducts research in data privacy for data to be used for machine and statistical learning. It is well known that data can be highly sensitive, and that naive anonymization is not sufficient to avoid disclosure. Models and aggregates can also lead to disclosure as they can contain traces of the data used in their computation. We want to understand the fundamental principles that permit us to build privacy-aware AI systems, and develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major journals on data privacy (Transactions on Data Privacy), and has active links with the private and public sectors. For more information see https://www. umu.se/en/research/groups/nausica-privacy-aware-transparent-decisions-group-/

The group collaborates with several national and international research groups on these topics, and has active links with the private and public sectors. For more information see: https://www.umu.se/en/research/groups/nausica-privacy-aware-transparent-decisions-group-/

The postdoctoral position is funded by WASP. Wallenberg AI, Autonomous Systems and Software Program (WASP) is Sweden’s largest individual research program ever, a major national initiative for strategically motivated basic research, education and faculty recruitment. The program addresses research on artificial intelligence and autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems.  The vision of WASP is excellent research and competence in artificial intelligence, autonomous systems and software for the benefit of Swedish society and industry. Read more: https://wasp-sweden.org/

Qualifications

To be appointed under the postdoctoral agreement, the postdoctoral fellow is required to have completed a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This qualification requirements must be fulfilled no later than at the time of the appointment decision.

To be appointed under the postdoctoral agreement, priority should be given to candidates who completed their doctoral degree, according to what is stipulated in the paragraph above, no later than three years prior. If there are special reasons, candidates who completed their doctoral degree prior to that may also be eligible. Special reasons include absence due to illness, parental leave, appointments of trust in trade union organisations, military service, or similar circumstances, as well as clinical practice or other forms of appointment/assignment relevant to the subject area. Postdoctoral fellows who are to teach or supervise must have taken relevant courses in teaching and learning in higher education.

Requirements:

• A PhD degree or a foreign degree that is deemed equivalent in Computer Science, or another subject of relevance for the project.
• Documented knowledge and proven research experiences in at least one of the areas of data privacy, machine learning, or language models is required.
• A successful candidate is expected to have a scientific and result-oriented approach to your work.
• A very good command of the English language, both written and spoken

Application

A full application should include:

• Cover letter describing your research interests and why you are applying for the advertised position. Include a summary of your qualifications, research interests, motivation for applying, and briefly describe the connection between your past research and the position (max 2 pages),
• Curriculum vitae (CV) with publication list,
• Verified copy of doctoral degree certificate or documentation that clarifies when the degree of doctor is expected to be obtained,
• Verified copies of other diplomas, list of completed academic courses and grades,
• Copy of up to 5 relevant articles,
• Other documents that the applicant wishes to claim.
• Contact information to two persons willing to act as references.

The application must be written in English or Swedish. The application is made through our electronic recruitment system. Documents sent electronically must be in Word or PDF format. Log in to the system and apply via the button at the end of this page. The closing date is March 19. Further details are provided by Vicenç Torra, vtorra@cs.umu.se