PhD student in Intelligent Edge Computing

Position Description
RISE offers this PhD position within the scope of the DAIS (Distributed Artificial intelligent systems) project, a pan-European effort with around 46 partners from 10 countries.

The position has a specialization in edge computing and machine learning. The main goal in the DAIS project is to provide intelligent, secure and trustworthy systems for industrial applications. DAIS will develop Edge hardware and software that is self-organizing, energy efficient, secure and private by design. DAIS will make sure Edge components are securely connected to the cloud and fog layers. Integrating edge with cloud and fog, includes areas like the orchestration and coordination of AI task running in different parts of the topology. To achieve this goal, a combination of different technologies and techniques such as Artificial Intelligence (AI), Machine Learning (ML), cybersecurity and Internet of Things (IoT) are considered in the project.

The project investigates efficient architectures and machine-learning algorithms for edge computing nodes in embedded systems for specific applications in medical, healthcare, automotive and robotics domains. Such edge computing nodes appearing in various sensor networks and IoT devices often need to process large amount of sensor data in real time and communicate via wired och wireless channels to external devices with high throughput. The problem is especially challenging because of limited resources in terms of area, power and storage and strict non-functional requirements on predictability and dependability in those embedded computing devices. This requires innovative architectures on which approximate machine learning algorithms can execute efficiently to perform runtime data analytic tasks such as data filtering, feature extraction and anomaly detection etc.

The project will be performed in close cooperation with partners from large industries, research institutes and universities, as well as small and medium-sized enterprises from both Sweden and other European countries. The doctoral program will be hosted by Mälardalen University, campus Västerås.

Place of employment: Västerås.

Full time 100% employment.

Employment available from beginning of August 2021.

In this role you will:

- Be part of a team that conducts applied research together with creative colleagues and in collaboration with both industry and the public sector;
- Develop methods and bring them into different application areas, in particular within smart industries;
- Be involved in planning and management of projects;
- Advocate research findings to diverse audiences through best suitable communication means: inspirational talks, demos, videos, presentations, and articles.

Minimum qualifications:

- Master's Degree (at least 240 credits) in computer science or computer networks or in a related field, from a recognized academic institution;
- Have experience or deep interest in distributed systems (Cloud/Fog/Edge), wireless communication, performance modelling or optimization, machine learning and artificial intelligence algorithms.

Preferred qualifications
As a candidate it is desirable that you:

- Have a background and experience in operations research, simulation, statistics, algorithms;
- Are curious, goal-oriented, flexible, ambitious and communicative;
- Are skilled in presenting and documenting your work in English, i.e., to describe the problem, the solution and the approach in an understandable manner;
- Have excellent programming skills (e.g. C, C++, Java and Python);
- Be able to read and understand state of the art research in computer networking, IoT, distributed systems (Cloud/Fog/Edge), and machine learning

Welcome with your application!
Do you have any questions or would like to know more? Please contact Dr. Ali Balador +46 73 053 21 33. Final application date is March 04, 2021. Interviews will take place continuously during the application period.

Applications should include a short CV (max 3 pages), one-page cover letter, complete transcript of records, and any letters of recommendation. The application should also include information on relevant previous work, industry experiences, bachelor's or master's thesis, scientific papers, or even outline of a thesis under submission. Incomplete applications will not be considered.

Our union contacts are for SACO; Ingemar Petermann, 010-228 41 22 and for Unionen; Linda Ikatti, 010-516 51 61.

We kindly ask external recruitment companies and sales people not to contact us as we are governed by the Swedish Procurement Act.

PhD student, Artificial Intelligence, Edge Computing, Machine Learning, IoT, Cybersecurity, RISE, Västerås