PhD Student in Informatics with a Specialization in Data Science, University in Skövde, Sweden


Deadline:

November 23, 2015


Opportunity Cover Image - PhD Student in Informatics with a Specialization in Data Science, University in Skövde, Sweden

The position is within Informatics, with a specialization in data science. At the University of Skövde Informatics is defined as the science that addresses how information is represented, processed and communicated in artificial and natural systems, and how such systems are used and developed in order to achieve usable and effective applications and solutions for individuals, organizations or society. Data science can overall be defined as the collection of theories, methods and techniques that all strive to convert large volumes of complex and heterogeneous data – so called big data – into knowledge that supports various decision-makers. Data science, thus, overlaps with traditional scientific disciplines, such as applied mathematics, information science, computer technology, statistics and computer science, along with a rapidly increasing number of application areas, e.g., business intelligence, biomedicine, textual analysis, geo-temporal analysis and medical and healthcare informatics.

Reference number: HS 2015/591

As one of the oldest and most prominent research groups in artificial intelligence (AI) in Sweden, the Skövde Artificial Intelligence Lab (SAIL) at the University of Skövde consists of about 15 researchers conducting research within applied AI in close collaboration with businesses and organizations. SAIL's research breaks down into two main research directions: 1) representations and algorithms for knowledge systems and decision support, and 2) visual analytics, specifically how user interactive visualization can support analytical processes. The group has extensive experience in many of the main methods and techniques within data science, e.g., data fusion, data mining, machine learning, predictive analytics, advanced programming, pattern recognition, uncertainty management and information visualization. The research is carried out within several projects, in close collaboration with partners such as AstraZeneca, Huawei and Saab. SAIL also plays a major role in the new Data Science master's programme, the first of its kind in Sweden.

The position comprises PhD studies (80 %) and departmental duties (teaching and administrative tasks, 20 %). Additional assignments might be included in the position. The doctoral student should contribute to on-going work and to the development of research within SAIL. The general area of research is data science. More specifically, the doctoral student is expected to contribute to several on-going SAIL projects by providing:

  • new knowledge of how different users use big data to solve today's analytical problems and what is needed to handle the big data problems of tomorrow,
  • new analytics methodology and high-level functionality for data analysis that make the value in big data more easily available to end-users,
  • new machine learning algorithms suitable for handling both the opportunities and challenges with massive, distributed and streaming data, and
  • new computation platforms suitable for analysis of massive, distributed and streaming data.

Depending on the student's background and preferences the research will be focused on one or more of the above objectives. Applications can similarly be found in one of several of SAIL's on-going projects such as business analysis, biomedicine, textual analysis, sports analytics or health care informatics.

Qualification requirements

The qualification requirements are:

  • an advanced level degree or at least coursework equal to 240 ECTS credits where a minimum of 60 ECTS credits is on the advanced level, or knowledge equivalent to these levels of university study
  • at least 120 ECTS credits of documented study within informatics, computer science or other potentially relevant subject area. At least 15 ECTS credits of the 120 ECTS credits should comprise a final year project on the advanced level
  • a passing grade on the Swedish senior high school course "English B" or equivalent.

Bases of evaluation

In addition to the qualification requirements, the bases of evaluation for this position are:

  • A good ability to do what is required for education on the PhD-level.
  • A good knowledge of machine learning or decision-support systems.
  • A good knowledge of modelling and analysis of big data.
  • A good knowledge of programming, especially for applications within data analytics.
  • Documented ability to cooperate with others and to work independently.
  • An ability to communicate well in English, orally and in written English.
  • A good ability to plan and organize one's workload.
  • A good ability to handle the demands and challenges of an academic environment.

For this position, special emphasis will be placed upon a good knowledge of machine learning or decision-support systems, a good knowledge of modelling and analysis of big data, a good knowledge of programming, especially for applications within data analytics as well as documented ability to cooperate with others and to work independently.

The PhD student is positioned at the School of Informatics, which is a school in expansion. Our research is internationally distinguished and our educational programs receive high rankings when it comes to both quality and cooperation with workplaces. Today there are 9 Professors, 12 PhD students and in total about 115 employees at the School of Informatics.

The University of Skövde strives towards ethnic and cultural diversity and equal gender distribution within all employment categories. As the majority of the employees in the subject area are men the University especially invites women to apply for this position.

The position is a temporary employment until PhD degree, but no longer than 5 years. Salary will be paid according to the local agreement "Salary ladder for PhD Students".

http://www.romstudyabroad.com/



Eligible Countries
Host Country
Study Levels
PhD
Opportunities
Publish Date
November 02, 2015
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