PhD student position in Machine-Learning-Enabled Embedded Control Systems - Befattningen är under tillsättning eller redan tillsatt, och det är inte längre möjligt att lämna in en ansökan

The Department of Applied Physics and Electronics currently has around 90 employees and conducts research in energy technology, laser spectroscopy, medical technology, electronics, and system engineering. For more information see www.tfe.umu.se/forskning/. 

We offer a PhD student position in Applied electronics with focus on Machine-Learning-Enabled Embedded Control Systems. Apply by 2019-06-06 at the latest.

Description of the PhD-Project
An Embedded Control System feature closed-loop, real-time interactions between an embedded computing system and a physical environment, and tight integration of computing, communication and control. Embedded Control Systems are often safety-critical systems that are subject to safety certification, e.g., ISO 26262 certification for passenger cars. While traditional control theoretic techniques, including PID Control, Model-Predictive Control, Optimal Control, have mature, rigorous design and analysis techniques that are capable of achieving high assurance, a novel class of control systems that include machine-learning algorithms in the loop are increasingly prevalent, e.g., Deep Reinforcement Learning, with its many and diverse applications ranging from AlphaGo to self-driving cars. In these and many other important applications, the control algorithms need to be implemented on embedded computing platforms with limited hardware resources due to cost and power constraints. Therefore, the system designer needs to make careful tradeoffs among multiple design objectives, incl. performance, cost, power, security, etc. This Ph.D. project aims to tackle the problem of how to achieve safety certification with machine learning in the loop, with main applications in self-driving cars and other potential applications of mobile robotic systems. This project addresses both design-time assurance with formal verification techniques, and runtime assurance with monitoring and enforcement of safety constraints.

Requirements
To be admitted for studies at third-cycle level 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 to be admitted for studies at third-cycle level in applied electronics with specialization in signal processing, the applicant is required to have completed course requirements of at least 120 ECTS credits within this field.

In addition, the applicant should, through university studies or other equivalent education, have gained basic theoretical knowledge in embedded systems and control theory, with applications in mobile robotics. The applicant must be able to work both independently and as part of a team, and, therefore, high focus will be given to the candidate’s potential collaborative skills. In addition to these requirements, candidates should have excellent skills in oral and written presentation in English.

Other desirable qualifications
Highly desirable knowledge and skills include: Machine Learning algorithms, incl. Reinforcement Learning and Deep Learning, as applied in Embedded Control Systems; Formal verification techniques, incl. Model-Checking, SAT Modulo Theories, MILP; Real-time Embedded Systems, incl. real-time scheduling algorithms and design optimization techniques. Knowledge of control theory or hands-on experience working with robotic platforms, is an advantage but not required.

Terms for the employment
The employment is expected to result in a doctoral degree and the main assignment for the doctoral student is thus to be part of the research education, which includes participation in the described research project but also to take relevant courses. Teaching and other departmental work (up to a maximum of 20%) can be included. The employment is limited to four years at full time. The salary is fixed according to the established salary level for doctoral students.

Application
Your application must include:

• a cover letter with a brief description of your qualifications, research interests and motivation for applying (max. 2 pages),
• a curriculum vitae (CV),
• copies of relevant degree diplomas and other certificates, a list of academic courses with grades (transcripts from B.Sc. and M.Sc. education),
• copies of your master thesis and any publications you authored or co-authored (if applicable),
• contact information for three academic reference persons

The application, including attached documents, must be written in English or Swedish. The application is made through our electronic recruitment system. The closing date is June6, 2019.

Information
Starting date: 2019-09-01 or according to an agreement.

For further information contact Professor Zonghua Gu, Tel. +4690 7866749, zonghua.gu@umu.se, or the head of the department Dr. Per Hallberg, Tel. +4690 7868062 per.hallberg@umu.se.

We are looking forward to your application!