Postdoctoral appointment in Computer Science for Data Science and AI - Hiring in process/Finished, not possible to apply

Description

The Faculty of Health Science and Technology has an opening for a full-time post-doctoral research fellow focused on software testing for data science and machine learning (ML). The position is available within 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 post-doctoral fellow will work in 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 ML to support new use cases including Industry 4.0, smart manufacturing, and real-time process control.

The post-doctoral fellow 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 objective is to build an automated real-time data verification strategy that decomposes the gathered data based on their context and then verify them according to predefined data rules. Having such a testing strategy will prevent the system from storing noisy and corrupted data, avoid the production of inaccurate or imprecise decision results, and ensure the system's quality while evolving over time.

With the collaboration of industrial partners and in this project, the post-doctoral fellow will help identify and understand practical challenges in this area and conduct research on the data to introduce testing strategies for the gathering and training data.

The following research directions will be investigated:

• Big data gathering, storage, management, and visualization.
• Dealing with missing and corrupted data, inaccurate or noisy data, data smoothing, and normalization.
• Feature engineering and ML Decision-making algorithms over networks.

A successful candidate will perform formal analysis as well as experimental validation of concepts in the context of industrial IoT systems to deliver reusable testing tools. 

Qualification requirements

To be eligible for the position, applicants are required to hold a recent PhD degree in computer science, software engineering, data science, computer engineering, mathematics, or electrical engineering (or equivalent qualifications). The candidate must have completed the degree no more than three years before the last date for applications unless special ground exists.

Assessment criteria

In the assessment procedure, emphasis will be placed on the applicant's scientific experience in relation to data science, software engineering, software testing, artificial intelligence, and machine learning, including:

• Strong software architectures and/or algorithms design/implementation/prototyping skills
• Hands-on experience/expertise in some of the following areas:

       - Data science, AI/ML techniques,

       - Automated software engineering, model-based testing, mutation testing,
         software testing strategies, or

       - Fault localization, prediction, and big data analysis,

• Publications in high impact journals and well-known conference proceedings,
• Oral and written communication skills in English,
• Ability to independently pursue his or her work, and
• Ability to collaborate with others 

Terms of employment

The position is a full-time position for one year with the possibility to extend for another year based on mutual agreement. The starting date for the position is within the time span of October 1, 2020 and January 1, 2021.

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

Application should include well documented qualifications. Applicants are responsible for submitting a complete application in accordance with the advertisement and for ensuring that the documentation allows for objective and qualitative assessments. A complete application should be submitted no later than the application deadline.

The application should include:

• Application letter with a brief description of your academic interests and how they relate to your previous studies and future goals. (Maximum 2 pages long)
• CV, including your relevant professional experience and knowledge and a list of your publications.
• 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.
• 2 representative publications or technical reports. For longer documents, please provide a summary (abstract) and a web link to the full text.
• Letter of recommendations.
• Contact information for two reference persons. 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 REK2020/169

Last day of application: 15 September 2020

We look forward to your application!

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