Umeå universitet, Department of Computing Science

Umeå University is one of Sweden’s largest institutions of higher education with over 35,000 students and 4,200 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.

At Umeå University, everything is nearby. Our cohesive campus environment makes it easy to meet, collaborate and exchange knowledge, which promotes a dynamic and open culture where we rejoice in each other's successes.

Research topic: Context Based Justification of Actions and Recommendations of Autonomous Systems

Umeå University, the department of Computing Science, is seeking outstanding candidates for a PhD student position in Computer Science with focus on allowing “blackbox” artificial intelligence methods (such as various Machine Learning methods, including Neural Networks) to justify their actions and recommendations to users, as well as to perform rationality and performance analysis of autonomous systems in different contexts. The need to be able to act in rational ways in different contexts is particularly relevant in mobile applications, such as autonomous cars. An autonomous car might need to be able to justify to the human driver why it suddenly proposes a route change, or posteriori justify its actions in a traffic accident.

The Department of Computing Science is a dynamic environment with around 100 employees representing more than 20 countries worldwide. We conduct education and research on a broad range of topics in Computing Science. The research will be performed under the supervision of Prof. Kary Främling (Data Science) and involves Artificial Intelligence and Machine Learning methods such as neural networks, Bayesian reasoning, natural language technologies, and cognitive sciences. The research will initially have connections with the H2020 project bIoTope (

The Wallenberg Autonomous Systems and Software Program (WASP)
The WASP program is Sweden's largest individual research program ever, and provides a platform for academic research and education, fostering interaction with Sweden's leading technology companies. The program addresses research on autonomous systems acting in collaboration with humans, adapting to their environment through sensors, information and knowledge, and forming intelligent systems-of-systems. WASP's key values are research excellence and industrial relevance.

The graduate school within WASP is dedicated to provide the skills needed to analyze, develop, and contribute to the interdisciplinary area of autonomous systems and software. The curriculum provides the foundations, perspectives, and state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. 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 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.

Research project
The project is a part of the establishing of a new team around the following high-level vision: Developing ground-breaking Data Science methods for Autonomous Systems that learn from data and experience and can justify and explain their behavior.

This PhD project will focus on the following topics:

  1. Decision Sciences: Modeling and learning of user and decision-maker actions and preferences in different contexts using non-linear machine learning methods such as neural networks. A challenge with such models is how they can justify their actions and recommendations, and how robust they are in different situations.
  2. Applying the same principles for justifying decisions, actions and recommendations of autonomous systems whose “intelligence” is based on machine learning and is therefore not directly explainable and understandable by humans.
  3. Developing and implementing methods for presenting such justifications and explanations in the most human-understandable way possible. Natural language is one possibility but modern human-machine interaction can also use graphics, sound, vibrations and other means for conveying the most relevant information to the users, while remaining as non-intrusive as possible.

 A high-level research plan can be summarized as enabling Self-* capable Intelligent Products and Environments, where Self-* signifies self-configuring, self-organizing, self-tuning, self-healing, self-managing and self-explaining systems.

 About the position
The successful applicant will receive a competitive salary for a period of four years full time research, provided that expected study and research results are achieved. The position may also include part-time teaching (normally up to 20%). If so, the total time for the position is extended accordingly (up to maximum five years). Expected starting date is 1st of April 2018 or as otherwise agreed.

 Admission requirements
The applicant is required to have completed 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 overseas, or equivalent qualifications. To fulfil the specific entry requirements for doctoral studies in computing science, the applicant is required to have completed courses at second-cycle level degree equivalent to 60 ECTS credits in computing science, or in a subject considered to be directly relevant for the specialisation in question.

Candidates are expected to have a background in computer science; a specialization in artificial intelligence or machine learning is a merit. Candidates from related disciplines, such as distributed web programming, with a very good understanding of fundamental concepts of computer science and good programming experience may also be considered. Due to the emphasis on human interaction and psychology, competencies in cognitive sciences and related topics could also be a major asset in this PhD project. Since research is conducted in an international research environment, the ability to collaborate and contribute to teamwork, and a very good command of the English language, both written and spoken, are key requirements.


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
  • If applicable, copy of completed BSc and/or MSc thesis and other original research publications
  • Copies of degree certificates, including documentation of completed academic courses and obtained grades
  • Contact information for two persons willing to act as references

Applications must be submitted electronically using the e-recruitment system Varbi, and be received no later than January 8, 2018. Reference number: AN 2.2.1-1783-17.

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. As we strive for a more balanced gender distribution within the department, we encourage women as applicants.

For additional information, please contact Prof. Kary Främling

We look forward to receiving your application!



Type of employment Temporary position longer than 6 months
Contract type Full time
Number of positions 1
Working hours 100%
City Umeå
County Västerbottens län
Country Sweden
Reference number AN 2.2.1-1783-17
  • Kary Främling, ,
Union representative
  • SACO, 090-786 53 65
  • SEKO, 090-786 52 96
  • ST, 090-786 54 31
Published 26.Oct.2017
Last application date 08.Jan.2018 11:59 PM CET

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