PhD student in Computational Science and Engineering with focus on Optimization for Federated Machine Learning

Umeå University is one of Sweden’s largest institutions of higher education with over 37,000 students and 4,800 faculty and staff. We are characterised by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison. Umeå University is also the site of the pioneering discovery of the CRISPR-Cas9 genetic scissors – a revolution in genetic engineering that has been awarded the Nobel Prize in Chemistry.

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To our department, characterized by world-leading research in several scientific fields and a multitude of educations ranked highly in international comparison, we now look for a doctoral student in computational science and engineering with a focus on optimization for federated machine learning. 

The Department of Computing science has been growing rapidly in recent years where focus on an inclusive and bottom-up driven environment are key elements in our sustainable growth. The 50 doctoral students within the department form of a diverse group from different nationalities, background and fields. If you work as a doctoral student with us you receive the benefits of support in career development, networking, administrative and technical support functions along with excellent employment conditions. See more information at:
https://www.umu.se/en/department-of-computing-science/

Is this interesting for you? Welcome with your application before 6th of November 2022.

Project description 

Because of privacy concerns around user data, and related legislation around handling user data, there has been an increased interest in using edge devices such as mobile phones, to process user data without storing them at a central location. This has also been a major concern in privacy-sensitive application areas of machine learning.

There has therefore been much interest in federated learning, a class of optimization algorithms used mainly to train a global machine learning model at disparate heterogeneous sites without sharing data between the sites. It is possible to frame federated learning as an operator splitting problem, and within the operator splitting framework, it is possible to simultaneously solve many of the problems that arise when training large-scale machine learning models on data from multiple sites.

The specific goals of this project are: to formulate the federated learning problem as an instance of operator splitting, to develop numerical optimization algorithms for these formulations, to analyze the theoretical convergence guarantees of these algorithms, to develop and analyze novel loss and penalty functions for the federated learning problem, and to scale these developments for large-scale machine learning tasks.

The doctoral student position is offered within a research project financed by the Wallenberg AI, Autonomous Systems and Software Program (WASP). The project is a collaboration between Tommy Löfstedt, Docent and Associate Professor at the Department of Computing Science, Umeå University, and Alp Yurtsever, Assistant Professor at the Department of Mathematics and Mathematical Statistics, Umeå University.

The Wallenberg AI, Autonomous Systems and Software Program (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 industry. Read more: https://wasp-sweden.org/ 

The graduate school within WASP provides foundations, perspectives, and state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. 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. The graduate school thus provides added value on top of the existing PhD programs at the partner universities, providing unique opportunities for students who are dedicated to achieving international research excellence with industrial relevance. 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 fulfill the specific entry requirements for doctoral studies in computational science and engineering, the applicant is required to have completed at least 90 ECTS credits in relevant fields for computational science and engineering (mathematics, mathematical statistics, and computing science), of which at least 30 ECTS credits are at second-cycle level. Applicants who in some other system either within Sweden or abroad have acquired largely equivalent skills are also eligible. 

Candidates are expected to have very good knowledge in project related areas, and in particular to have a very strong documented background in optimization theory. A very good command of the English language is also a key requirement. The candidates must also have strong programming skills. Documented knowledge and experience in numerical methods, federated learning, and machine learning are merits.

Important personal qualities are good communication skills, the ability to work on your own as well as together with others, ability to quickly grasp new concepts and place them in context, to be creative, and to have a will to actively develop yourself to become a competent researcher.

The merits of a selected candidate will also be evaluated by WASP, who will consider the candidate’s grades in education programs of relevance with a focus on grades in courses that are at the core of WASP and the project area. WASP will also consider whether the candidate has a background and experiences within the WASP areas, and if the candidate is sufficiently motivated for PhD studies within WASP. These criteria are therefore also part of our criteria when ranking candidates.

About the position

The position provides you with the opportunity to pursue PhD studies in Computational Science and Engineering for four years, with the goal of achieving the degree of Doctor in Computational Science and Engineering with a specialization 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 employment starts in January 2023 or according to agreement.

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, why you are interested in the WASP doctoral school. The letter should include a (documented) description of how you fulfill the specified requirements, and should also contain your contact information.
• A curriculum vitae (CV).
• Certified copies of degree certificates (for both BSc and MSc, if applicable), including documentation of completed academic courses and obtained grades.
• Copies of completed BSc and/or MSc theses and other relevant publications, if any.
• Documentation and description of other relevant experiences or competences.
• Contact information to three references.

The application must be written in English or Swedish. Attached documents in other languages should be translated. 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 6th of November 2022.

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 associate professor Tommy Löfstedt ([email protected]) or assistant professor Alp Yurtsever ([email protected]).

We look forward to receiving your application!