PhD student in Computing Science with focus on data privacy

Umeå University is one of Sweden’s largest higher education institutions with over 37,000 students and about 4,700 employees. The University offers a diversity of high-quality education and world-leading research in several fields. Notably, the groundbreaking discovery of the CRISPR-Cas9 gene-editing tool, which was awarded the Nobel Prize in Chemistry, was made here. At Umeå University, everything is close. Our cohesive campuses make it easy to meet, work together and exchange knowledge, which promotes a dynamic and open culture.

The ongoing societal transformation and large green investments in northern Sweden create enormous opportunities and complex challenges. For Umeå University, conducting research about – and in the middle of – a society in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here.

The Department of Computing Science is now looking for a Doctoral student in Computing Science with a focus on data privacy. 

The department has been growing rapidly in recent years. An inclusive and participatory environment are key elements in our growth. The 60 doctoral students within the department are a diverse group from different nationalities, backgrounds and fields. We offer very good employment conditions, and administrative and technical support, among other benefits. See more information at:
https://www.umu.se/en/department-of-computing-science/ 

Is this interesting for you? Welcome with your application before 2024-06-21 

Project description  

The project will develop privacy-aware machine learning (ML) models. We are interested in building models that are explainable and are extracted from complex and heterogeneous data. Within explainable ML, we are interested in topics as provenance, interpretable and transparent models. 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. Other topics of interest for this project are: aggregation, voting, game theory, and graph theory.  

Research group 

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-/ 

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 industry. Read more: https://wasp-sweden.org/  

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of artificial intelligence, autonomous systems and software. Through an ambitious program with research visits, partner universities, and visiting lecturers, the graduate school actively supports forming a strong multi-disciplinary and international professional network between PhD-students, researchers and industry. Read more: https://wasp-sweden.org/graduate-school   

Admission requirements  

The general admission requirements for doctoral studies are a second- cycle level degree, or completed course requirements of at least 240 ECTS credits, of which at least 60 ECTS credits are at second-cycle level, or have an equivalent education from abroad, or equivalent qualifications. To fulfil the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed at least 90 ECTS credits in computing science.   

You should have very good knowledge and skills in programming with a focus on efficient implementation of algorithms, and good knowledge of mathematics and/or statistics. You should also be able to speak and write English fluently.   

In addition to creativity and an inquisitive mind, important personal qualities are the ability to work both independently and in a team, as well as experience in international cooperation.  

It is an advantage if you have documented knowledge and experience in machine learning and in mathematical/logical problem formulation (e.g. optimization, game theory, graph theory). 

About the position 

The position provides you with the opportunity to pursue PhD studies in Computing Science for four years, with the goal of achieving the degree of Doctor in Computing Science. While the position is mainly devoted to PhD studies (at least 80% of the time), it may include up to 20% department service (usually teaching). If so, the total time for the position is extended accordingly, resulting in a maximum of five years. 

The procedure for recruitment for the position is in accordance with the Higher Education Ordinance (chapter 12, 2§) and the decision regarding the position cannot be appealed. 

The expected starting date is 2024-08-15 or as otherwise agreed. 

Application 

Applications must be submitted electronically using the e-recruitment system of Umeå University. 

A complete application should contain the following documents: 

• A cover letter including a description of your research interests, your reasons to apply for the position, and your contact information. Describe in your cover letter your experience on machine learning, mathematics, statistic or logic that may be relevant for the project.  
• A curriculum vitae  
• Reprints / copies of completed BSc and/or MSc theses and other relevant publications, if any 
• Copies of degree certificates, including documentation of completed academic courses and obtained grades  
• Documentation and description of other relevant experiences or competences. 

The application must be written in English or Swedish. Attached documents must be in pdf format. Applications must be submitted electronically using the e-recruitment system of Umeå University, and be received no later than 2024-06-21. 

The Department of Computing Science values gender diversity, and therefore particularly encourages women and those outside the gender binary to apply for the position. 

For additional information, please contact professor Vicenç Torra ([email protected]).