Ph D student position in Data Science

Updated: about 22 hours ago
Deadline: 28 Feb 2020

Research topic: Explainability ofAutonomous Systems based on Machine Learning

Umeå University, the Department of Computing Science, is seeking outstanding candidates for a PhD student position in Data Science with. Deadline for applications is February 28.

The Department of Computing Science is a dynamic environment with more than 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.

KAW and WASP
The project is financed by the Knut and Alice Wallenberg foundation (KAW). The intention is that the student will be associated to the WASP-AS (see https://wasp-sweden.org/about-us/wasp-as/) or WASP-AI graduate program (see https://wasp-sweden.org/about-us/wasp-artificial-intelligence/). The graduate schools within WASP provide foundations, perspectives, and state-of-the-art knowledge in the different disciplines taught by leading researchers in the field. It 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.

Research project
The PhD student should have a focus on machine learning methods for detecting and predicting anomalies in autonomous systems and machines, as well as methods for improving the performance of such systems. The need to act rationally in a variety of different contexts is particularly relevant for applications involving physical assets, such as autonomous cars. In such systems the reliability, robustness, stability and self-assessment capabilities are crucial for their safe operation. Explainability and justification of actions to end users are crucial in order to achieve and maintain end-user confidence and trust in such systems.

This PhD project will focus on the following topics:

  • Intelligent control: Use Machine 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.
  • Explainable AI (XAI) in real-world environments and applications. Active collaboration with industrial partners will be encouraged and facilitated, as well as real-world implementations for smart factories, smart cities, smart homes, smart mobility etc.
  • 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 May 2020 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. 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.

    Application
    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 February 28, 2020. Reference number: AN 2.2.1-79-20.

    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 [email protected]

    We look forward to receiving your application!


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