PhD student in Computing Science with focus on machine learning for continuous and discrete structures

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 machine learning for continuous and discrete structures. 

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/

Interested? We welcome your application until 2024-05-02.

 Project description

The focus of the project is graph based machine learning for discrete and continuous structures, led by Frank Drewes, Johanna Björklund, and Henrik Björklund.

The PhD student will work within the context of the STING (Synthesis and Analysis with Transducers and Invertible Neural Generators) project, financed by WASP (Wallenberg AI, Autonomous Systems and Software Program). The project conducted in collaboration with the Royal Institute of Technology (KTH) in Stockholm and Lindköping University.

Human communication is multimodal in nature, and occurs through combinations of speech, language, gesture, facial expression, and similar signals. STING aims to design models that capture this richness, uniting synthesis and analysis with the help of both discrete and neural models. Covering both synthesis and analysis in one framework also allows us to create efficient mechanisms for explainability, and to inspect and enforce fairness in the models.

We ourselves are experts on discrete models for graph generation, and have recently started to apply these to the task of parsing multimodal language data. We also work on bias analysis and mitigation. The partner research groups bring complementary expertise to the project: KTH has extensive experience with probabilistic deep learning for analysis and synthesis of human communication. Linköping University complements these aspects with in-depth knowledge of natural language processing.

In addition to its scientific value, the technologies developed by the project are expected to have a substantial societal imprint. Read more about the NEST project at:

https://wasp-sweden.org/sting-synthesis-and-analysis-with-transducers-and-invertible-neural-generators/

The research focus of the doctoral student within the spectrum covered by STING will be determined based on the scientific background and interests of the selected candidate. The project is conducted within the research group for the Foundations of Language Processing at Umeå University. The group studies theoretical and practical aspects of representing language on computers, and its interconnection with other sources of information. The work of the group spans from formal language theory to applied natural language processing. The group consists of five senior researchers and eight PhD students. More information is available at:

https://www.umu.se/en/research/groups/foundations-of-language-processing/

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.

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. Because of the interdisciplinary nature of the project, 30 of these 90 ECTS credits can be replaced by credits in other subjects relevant to the project, such as, e.g., computational linguistics. Applicants who otherwise have acquired skills that are deemed equivalent are also eligible.

Candidates are expected to have very good knowledge in at least one of:

• Formal language theory
• Machine learning

Other desirable qualifications include experience in

• Natural language processing
• Formal graph languages
• Graph representation learning
• Empirical methods, i.e., formal hypothesis testing

As a person, you are curious and interested in working together with others towards common goals.

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.

Start date June 2024 or according to agreement.

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.

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
• A curriculum vitae
• Reprints / copies of completed BSc and/or MSc theses and other relevant publications, if any
• Copies of degree certificates, including an official transcript of completed academic courses and obtained grades
• Documentation and description of other relevant experiences or competences.
• Names and contact information of at least two reference persons

The application must be written in English or Swedish. Attached documents must be in pdf format. Applications must be received no later than 2024-05-02.

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 Johanna Björklund ([email protected], Umeå universitet), Henrik Björklund ([email protected] , Umeå universitet), or Frank Drewes ([email protected] , Umeå universitet).

We look forward to receiving your application!