PhD student in Computer Science for/with-focus-on explainable AI and AI

Mälardalen University

Sweden

December 7, 2021

Description

PhD student in Computer Science for/with-focus-on explainable AI and AI

Västeras

At Mälardalen University people meet who want to develop themselves and the future. We have 19 900 students reading courses and study programmes in Business and Economics, Health, Engineering and Education at our campuses in Eskilstuna and Västerås, or by distance. We conduct research within all fields of education and have internationally prominent research in Future Energy and Embedded Systems. Our close collaboration with the private and public sectors enable us at MDH to contribute towards the better health of people and towards a more sustainable planet.

At the School of Innovation, Design and Engineering our students are studying to be for example innovators, entrepreneurs, illustrators, communications officers, network technicians and engineers. Here we have the research specialisations of Embedded Systems, and Innovation and Product Realisation. Our work takes place in cooperation with and in strategic agreements with companies, organisations and public authorities in the region.

Employment information

Employment: Temporary employment Scope: Full time Closing date for application: 2021-12-07 Campus location: Västeras School: School of Innovation, Design and Engineering, (IDT)

Position description

For this position, research will be conducted within project CPMXai – Cognitive Predictive Maintenance and Quality Assurance using Explainable Ai and Machine Learning.

CPMXai aims to develop a digital twin for cognitive predictive maintenance through automatic data labelling, AI/ML and Explainable AI (XAI) to reduce unwanted situations and enhance maintenance in manufacturing and production processes. CPMXai has 3 objectives i.e., 1) identify use cases in the industries, 2) develop a new automatic data labelling tool with the help of digital twin and lastly, 3) develop a self-monitoring, self-learning, self- explainable system to predict.

CPMXai is a Production 2030 project funded by Vinnova comprises with 8 different partners including 5 industries in Sweden.

The position focus is on computer vision, image processing, advanced data analytics, machine learning, artificial intelligence, and signal processing; as well as data modeling for digital twin and cognitive predictive maintenance. The work requires theoretical studies on the state of art, together with software development and testing. As a PhD student, you are expected to develop independent ideas and to communicate research results in oral and written form. The employment includes collaboration and co-production within the industrials' partners.

Qualifications

Only those who are or have been admitted to third-cycle courses and study programmes at a higher education may be appointed to doctoral studentships. For futher information see Chapter 5 of the Higher Education Ordinance (SFS 1993:100).

The applicant must have a B.SC/M.Sc. or four years of study (240 higher education credits) with at least one year (60 credits) at second-cycle degree in Electrical and Computer Engineering. Proficiency in English, both written and oral, is required.

Knowledge/experience in artificial intelligence, machine learning, and deep Learning and knowledge/experience in computer vision and image processing is required.

Extensive programming experience is required, e.g., knowledge of Python, MATLAB, Tensorflow, Keras, Pandas, OpenCV, PHP, and SQL/MySQL.

Knowledge/experience in data analytics using artificial intelligence, machine learning, deep Learning based on signal data e.g. CT images, X-Ray Images, Spiral Drawing signals, IoT LoRa technology and Hybrid CNN-PCA Based Feature Extraction is required.

Decisive importance is attached to personal suitability. We value the qualities that an even distribution of age and gender, as well as ethnic and cultural diversity, can contribute to the organization.

Merit

Experience as a research engineer in the area of artificial intelligence.

Experience in Journal Publications e.g. IEEE Access.

Honors, and Awards are considered of merit.

Application

Application is made online. Make your application by clicking the "Apply" button below.

The applicant is responsible for ensuring that the application is complete in accordance with the advertisement and will reach the University no later than closing date for application.

We look forward to receiving your application.

Contact person

Shahina Begum

Associate professor

+46 (0) 21 10 73 70

Susanne Meijer

Union representative (OFR)

+46 (0) 21 10 14 89

Michaël Le Duc

Union representative SACO

+46 (0) 21 10 14 02

URL to this page

https: // web103.reachmee.com/ext/I018/1151/main?site=8&validator=2efd9e54ee423d53334ac7960e3b4e03〈=UK&rmpage=job&rmjob=1376&rmlang=UK

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