PhD Student Position in Computer Science, Umeå
PhD Student Position in Computer Science Umeå universitet, Institutionen för datavetenskap
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Research topic: Context Based Machine Learning for Autonomous Systems
Umeå University, the department of Computing Science, is seeking outstanding candidates for a PhD student position in Computer Science with focus on machine learning methods for autonomously learning optimal or “sufficiently good” actions to take 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. However, context changes can happen in most application areas, such as manufacturing where a machine breakdown or similar may introduce new situations that need to be managed successfully.
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, rule-based reasoning, semantic networks, and reinforcement learning, as well as distributed multi-agent systems. The research will initially have connections with the H2020 project bIoTope (http://www.biotope-project.eu/).
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. http://wasp-sweden.org/
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:
- Intelligent control: Use principles of reinforcement learning and related technologies targeted towards self-learning and adaptive control.
- Embedded intelligence: Emphasis would be on augmenting the product intelligence embedded in products so that they can auto-adapt themselves according to their operating conditions, communicate with other products and adapt to them, as well as access and use external information systems that are relevant to them.
- Autonomous agents and multiagent systems for implementing Cyber-physical systems (CPS) in a Systems of Systems (SoS; see e.g. https://ec.europa.eu/digital-single-market/en/system-systems) setting. CPS also takes into consideration the human factor, as well as society as a whole.
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, and self-managing systems. Future work is expected to have a significant role in the development of such Self-* systems through IoT-enabled remote monitoring and updating over standardized interfaces, together with novel machine learning methods and algorithms are the main technical enablers of such 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.
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. Experience from Internet of Things (IoT), or research projects relating to IoT is also a merit. 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 2.2.1-1782-17.
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 Kary.Framling@umu.se
We look forward to receiving your application!
Umeå University wants to offer an environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development.
In each recruitment we aim to increase diversity and the opportunity to affirmative action.
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Type of employment: Temporary position longer than 6 months
Contract type: Full time
First day of employment: Expected starting date is 1st of April 2018 or as otherwise agreed
Salary: Monthly salary
Number of positions: 1
Working hours: 100%
County: Västerbottens län
Reference number: AN 2.2.1-1782-17
- Kary Främling, email@example.com
- SACO, 090-786 53 65
- SEKO, 090-786 52 96
- ST, 090-786 54 31
Last application date: 08.Jan.2018 11:59 PM CET