The Department of Computing Science, Umeå University (http://www.cs.umu.se/english/) is seeking outstanding candidates for one postdoctoral researcher position within the field of data mining/knowledge systems, especially on heterogeneous data integration and knowledge federation. We are looking for a skilful researcher, who is able to contribute to our research environment through independent and innovative research, cooperate with other researchers, and assist in the supervision of PhD students. The successful candidate will join a recently funded project at Umeå University on academic federated knowledge base construction.
Application submission deadline is February 2018-02-28.
This project is focusing on creating an infrastructure for academic federated knowledge bases by integrating major research data sources at the university, like the demographic data, health databases, and a number of national data sources as well as public web data sources (i.e., social media data). This initiative is in line with the investigation that the Swedish government recently initiated, where Umeå University is mentioned as a core partner in the anticipated technology development in this area.
The federated knowledge base would be a virtual integration of individual data sources which may be large, distributed, heterogeneous, and autonomous. During the construction and federation process, it is of interest to explore academic and practical research topics, such as natural language query optimization, entity resolution and privacy preservation. Technology used will include data mining, data analysis, natural language processing, machine learning, and data visualization.
The appointment is for two years full time contract. It is expected to start from April 1, 2018, or as otherwise agreed.
Qualifications The applicant must have a PhD degree or a foreign degree that is deemed equivalent to a PhD in computer science or another subject relevant for the project. The PhD degree shall not be more than three years old by the end of the application period unless there are special reasons.
In particular, the applicant must have a background in the area of data mining, data analysis, and database, especially on heterogeneous data integration, knowledge federation and system design. In the selection of candidates, attention is paid to both academic and practical skills. Experience of privacy protection is a requirement.
Programming proficiency in objective languages and script languages (e.g., Python, Java) are merits. Ability and experience of applying open source software (e.g., Spark, Mysql etc.) is also a merit. Good research merits and publications on data mining, natural language processing, machine learning, database system, knowledge federation or relevant areas for the position are strongly meriting. Excellent communication skills in both written and spoken English are required.
Application A complete application should include:
Please observe that all material needs to be in Swedish or English (translations of documents in other languages).
More information For enquiries and more information, please contact Assistant Professor Lili Jiang (email: email@example.com).
Welcome with your application! Applications must be submitted electronically using the e-recruitment system MyNetwork Pro, and be received no later than February 28th, 2018. Reference number: AN 2.2.1-1280-17
More about us The Department of Computing Science is a dynamic environment with around ninety employees representing more than ten countries worldwide. We conduct education and research on a broad range of topics in Computing Science.
Umeå University wants to offer an environment where open dialogue between people with different backgrounds and perspectives lay the foundation for learning, creativity and development. We offer a wide variety of courses and programs, world leading research, and excellent innovation and collaboration opportunities. More than 4 300 employees and 31 500 students have already chosen Umeå University. In each recruitment, we aim to increase diversity and the opportunity to affirmative action. In particular, we encourage female applicants!
We kindly decline offers of recruitment and advertising help.
We look forward towards receiving your application!
2018-04-01 or as otherwise agreed
Lili Jiang, Ass.prof
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