Karlstad University / Department of Mathematics and Computer Science

Description 

A PhD position in computer science, focused on software testing for data science and machine learning with the Software Quality and Digital Modernisation (SQuaD) research group at the Department of Mathematics and Computer Science, Karlstad University. SQuaD is a newly established and motivated group at the department. It aims to develop methods and techniques to continuously preserve, improve, and adapt quality attributes of long-living software systems to allow such systems to be maintained and to evolve more efficiently.

The Department of Mathematics and Computer Science consists of two research subjects: Mathematics and Computer Science. It has a research and teaching staff of more than 60 persons. In Computer Science, research and education are focused on computer networking and distributed systems, computer security and privacy, and software engineering. Both research and education are conducted in close cooperation with international, national and regional partners from both academia and industry.

Duties

The PhD position is linked to the new AIDA project, an industrial collaboration project funded by the Knowledge Foundation of Sweden. AIDA aims to develop a framework for next-generation Industrial Internet of Things (I-IoT), where software defined time sensitive networks interact with real-time edge compute and machine learning (ML) to support new use cases including Industry 4.0, smart manufacturing, and real-time process control.

The candidate will help establish the global aim of the AIDA project to enable trustworthy data-driven real-time industrial IoT applications by building a testing strategy that contributes towards reliable decision-making. The testing strategy will consider the continuous evolution of the system and the unpredictable behavior of the ML algorithms. The candidate will design and implement a real-time testing strategy that evaluates the system's correctness based on automated testing oracles and conducting empirical studies on several strategies that can be applied for the correctness testing within real industrial IoT systems. This will also include the implementation of a real-time test generation, execution, and bug report for deep learning systems, taking into account the internal algorithm structure.

The candidate should have a strong background and interest in optimization, ML, and software testing. It is required that the candidate has excellent programming skills and proficiency in the English language (written and spoken). The candidate is expected to work independently, as well as in teams. A majority of the work will be done in cooperation with other scientists and engineers from the industry. It is therefore desirable that the candidate can perform well in collaborative work and has experience working in projects.

The successful candidate will perform formal analysis and experimental validation of concepts in the context of industrial IoT systems to deliver reusable testing tools and publish the output results in refereed venues such as journals, conferences, and workshops.

Eligibility

Eligible for this position are candidates that meet the general admission requirements as well as the specific admission requirements and be judged to have the ability otherwise required to pursue the program successfully.

A person who has earned a Master’s degree of at least 240 ECTS credits of which at least 60 ECTS credits are earned for studies at master’s level, or who in some other way in the country or abroad has acquired largely equivalent knowledge, has general eligibility for admission.

A person with a Master’s degree (60 credits) in computer science, a Master’s degree (120 credits) in computer science or a Master of Science degree in computer technology has special eligibility for admission to doctoral studies in computer science. A person who has acquired equivalent qualifications in some other way in the country or abroad also has special eligibility.

Admission and assessment criteria

For admission to doctoral studies, an applicant must be judged to have the ability required to pursue the program successfully (Higher Education Ordinance, Ch. 7, sect. 35). Admission is based on individual assessment of the candidates’ abilities to pass the research education successfully.

In order to succeed as a doctoral student at Karlstad University, the candidate need to be goal-oriented and persevering in their work. In the selection of the applicants, the following will be assessed:

- ability to independently pursue their work,

- ability to collaborate with others,

- have a professional approach, and

- analyse and work with complex issues.

After the qualification requirements, great emphasis will be placed on personal qualities and personal suitability.

Terms of employment

Upon admission to doctoral studies, a studentship position will be offered (Higher Education Ordinance, Ch. 5, sect.3). The position is a full-time, fixed-term employment (one year that can be extended by two years at the most at a time) with starting-date by agreement.

Further information

Karlstad University places great value on the enriching presence of diverse backgrounds and gender balance in the organisation. We welcome applicants with different cultural backgrounds, gender identities, functional abilities, and life experiences.

Application

Your application should include well documented qualifications. Applicants are responsible for submitting a complete application in accordance with the advertisement before deadline and for ensuring that the documentation allows for objective and qualitative assessments. An incomplete application may jeopardise a fair assessment of qualifications.

Applications should include
• Application letter with a brief description of what your academic interests are and how they
relate to your previous studies and future goals. (Maximum 2 pages long)
• CV including your relevant experience and knowledge and a list of your publications (if
applicable).
• Copy of the degree certificate(s) and transcripts of records from your previously attended
university-level institutions. Translations into English or Swedish if the original documents are not
issued in one of these languages.
• Copy of a Master thesis (one or two years) or equivalent,
• Copies of publications or certificate of other qualifications, if applicable
• A letter of recommendation.
• Contact information for two reference persons, of which at least one is a former or present supervisor, or equivalent. We reserve the right to contact references only for shortlisted candidates.

Submit your application via the University’s web based recruitment tool and attach all the documents and publications you wish to be considered to the electronic application (do not provide links to them). A complete application should be submitted no later than the application deadline.

Documents that cannot be sent electronically such as books and other publications should be sent to:
Karlstads universitet
Registrator
651 88 Karlstad
State the ref.no REK2020/168

Last day of application: 15 September 2020
We look forward to your application!


Karlstad University has chosen advertising channels for this recruitment and declines any contacts from advertising or recruitment agencies.

Type of employment Temporary position
Contract type Full time
First day of employment By agreement
Salary Monthly
Number of positions 1
Full-time equivalent 100 %
City Karlstad
County Värmlands län
Country Sweden
Reference number REK2020/168
Contact
  • Stefan Lindskog, 054 700 1152
  • Bestoun S Ahmed Al-Beywanee, 054 700 1861
Union representative
  • Thomas Bragefors, SACO, 054 700 1714
  • Denita Gustavsson, OFR, 054 700 1434
  • Tony Ingemarsson, Lärarförbundet, 054 700 1404
Published 13.Jul.2020
Last application date 15.Sep.2020 11:59 PM CEST

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