PhD student in Computer Science for Data Analytics

Ref number: 2017/1571
Employment: Temporary employment - 4 years
Closing date for application: 2017-08-15
Scope: Full time
Campus location: Västerås
School: Innovation, design and engineering

MDH in Eskilstuna and Västerås is one of Sweden’s biggest university colleges with its 15 000 students and 900 employees. It has a long tradition of cooperating with society and has entered strategic agreements with both the public and the private sector. Most study programmes fall into four main areas: economy, health and welfare, education, and technology. With its research, which often takes the form of co-production on the regional, national and global levels, MDH aims to generate useful solutions for societal development. In 1999, MDH was the world’s first university to be environmentally certified, and in 2006, it was the first higher education institution in Sweden to be certified for its work environment.

Position description  

Research will be conducted within project SimuSafe – Simulator of behavioral aspects for safer transport. The goal of the project is, by a combination of artificial intelligence, intelligent sensing, and virtual reality, to retrieve accurate agent and behavioral models in a transit environment, and to reproduce these in a traffic simulator. The purpose is to determine cause and consequence in incidents of interest, and to understand the underlying behaviors and motivations of the involved agents. MDH will lead a work package with the aim of providing data analytics and metric computation functionality for different agent models, such as car, pedestrian, and bicycle. This includes neurometric indexes of risky attitudes and behaviors based on physiological parameters (HR/HRV, EMG, EEG; EOG, ECG and GSR) coupled with contextual information (e.g., sleep duration/quality, activity intensity, weather, noise) in order to assess risk perception, awareness, attention and decision-making.

The position focus is on advanced biomedical signal processing and sensor signal abstraction, e.g., electrocardiography (ECG) and electroencephalography (EEG), as well as data modeling and simulation environment integration. 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 both nationally and internationally.

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 should have a master degree, or equivalent, in Computer Science. Proficiency in English, both written and oral, is required.

Knowledge/experience in artificial intelligence, machine learning, and signal processing is required. Experience of multi-sensor fusion and big data analytics is of high merit.

Extensive programming experience is required, with knowledge of Java, MATLAB, and data analysis platforms such as Hadoop, being of high merit.

Professional experience and/or domain knowledge of physiological signal analysis in human monitoring is considered of merit. 

Information

Information can be provided by project leader Mobyen Uddin Ahmed, +46 (0) 21 10 73 69.

The union representatives are Susanne Meijer, (OFR), +46 (0) 21 10 14 89 and Michaël Le Duc, (SACO), +46 (0) 21-10 14 02.

We decline all contact with recruiters and salespersons of advertisements. We have made our strategic choices for this recruitment.

Application

An application prepared in English should contain:

  1. Short CV: data about yourself including date of birth, sex, address, e-mail address if possible.
  2. Copy of an official document giving grades from your undergraduate degree(s) or studies.
  3. A description of:
    a) an area of interest within your chosen subject(s) and maybe plans for research if any
    b) previous work and teaching experience if any
    c) previous PhD studies, also in other subjects.
  4. If possible, some letters of recommendation from people who know you as a student or as an employee.
  5. Any scientific papers you may have written (Master´s thesis, project report etc).
  6. Other relevant information.

To apply, please send your application by e-mail to the address ansokan@mdh.se. Application sent electronically should be in Word or PDF format.

You can also send your application to the following address:

Mälardalens högskola (Mälardalen University)
Personalsektionen (Division of Human Resources)
Jan Romedahl
Box 883
721 23 Västerås

Please state the reference number 2017/1571 in your application.

The applicant is responsible for ensuring that the application is complete in accordance with the advertisement and will reach the University no later than 2017-08-15.

We look forward to receiving your application.