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PhD Research Fellow in Automated and Intelligent Dataflow Management
Universitetet i Oslo
The University of Oslo is Norway’s oldest and highest rated institution of research and education with 28 000 students and 7000 employees. Its broad range of academic disciplines and internationally esteemed research communities make UiO an important contributor to society.
The Department of Informatics (IFI) is one of nine departments belonging to the Faculty of Mathematics and Natural Sciences. IFI is Norway’s largest university department for general education and research in Computer Science and related topics.
The Department has more than 1800 students on bachelor level, 600 master students, and over 240 PhDs and postdocs. The overall staff of the Department is close to 370 employees, about 280 of these in full time positions. The full time tenured academic staff is 75, mostly Full/Associate Professors.
About the position
Position as PhD Research Fellow in Automated and Intelligent Data Flow Management is available at the Department of Informatics, University of Oslo.
The position is in the context of a new project, funded by the Research Council of Norway, called Efficient Recycling of E-Waste through Automated and Intelligent Resource Dataflow (REWARD).
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date preferably no later than January 15, 2024.
The fellowship period is three years and devoted to carrying out research in the context of the REWARD project. The research is conducted in collaboration with Norwegian Institute for Air Research (NILU) and other project partners, both from academia and industry.
A fourth year may be considered with a workload of 25 % that may consist of teaching, supervision duties, and/or research assistance. This is dependent upon the qualification of the applicant and the current needs of the department.
More about the project and PhD position
The rapid technological advances with increasing application of ICT, e.g., Internet of Things (IoT) devices, have accelerated the generation of electronic waste (e-waste). For effective e-waste management, significant efforts have been made on generation and collection of data rather than the application, integration, and interpretation of e-waste data. This has led to creation of islands of propriety data, resulting in limited interoperability among stakeholders. With increasing digitalization and advancing technologies, the dynamics of e-waste flows is also expected to evolve further leading to increased complications and cost in e-waste recycling businesses.
The main objective of REWARD is to provide an integrated information infrastructure to systematically identify reusable and recyclable materials in e-waste products while determining the associated social, environmental, and economic (SEE) dimensions of circularity interventions. In REWARD, the data on e-waste generation and e-waste resources, along with SEE parameters will be fed to the integrated information infrastructure to facilitate automated cross-organization data interpretation and integration, and identifying optimal e-waste recycling options among relevant actors.
The main goal of the announced PhD position is to design and develop a data flow infrastructure for e-waste resources in the REWARD information system. Ontology and semantic data modeling and processing will be applied for the classified data of e-waste resources to create the main building blocks of the data flow infrastructure. Relevant semantic-based data matching algorithms will be used for automated integration. Beyond that, machine learning techniques will be used to predict e-waste generation to enhance the semantic models for future integration scenarios.
The Faculty of Mathematics and Natural Sciences has a strategic ambition to be among Europe’s leading communities for research, education and innovation. Candidates for these fellowships will be selected in accordance with this, and expected to be in the upper segment of their class with respect to academic credentials.
- Applicants must hold a master’s degree or equivalent in Computer Science or Information technology
- Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system
- Fluent oral and written communication skills in English
- The candidate should have interest and background in data modeling, data integration, semantic data modeling, and ontologies
- The candidate must have good analytical skills and programming experience (e.g., Java or python)
- It is desirable that the candidate has good knowledge on Machine Learning
- Applicants must be able to demonstrate interest in scientific research
- The evaluation considers many aspects of excellence, as well as the personal drive and organizational skills
The norm is as follows:
- The average grade point for courses included in the Bachelor’s degree must be C or better in the Norwegian educational system
- The average grade point for courses included in the Master’s degree must be B or better in the Norwegian educational system
- The Master’s thesis must have the grade B or better in the Norwegian educational system
- English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements
The purpose of the fellowship is research training leading to the successful completion of a PhD degree.
The fellowship requires admission to the PhD programme at the Faculty of Mathematics and Natural Sciences. The application to the PhD programme must be submitted to the department no later than two months after taking up the position.
For more information see here.
- Salary NOK 532 200 – 575 400 per annum depending on qualifications as PhD Research Fellow (position code 1017)
- Attractive welfare benefits and a generous pension agreement
- Vibrant international academic environment
- Career development programmes
- Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
How to apply
The application must include:
- Cover letter - statement of motivation and research interests
- CV (summarizing education, positions and academic work - scientific publications)
- Copies of the original Bachelor and Master’s degree diploma and transcripts of records
- Documentation of English proficiency if applicable
- Copies of 2-3 letters of recommendation
The application with attachments must be delivered in our electronic recruiting system (please follow the link “Apply for this job”). Foreign applicants are advised to attach an explanation of their University's grading system. Please note that all documents should be in English or a Scandinavian language.
Interviews with the best qualified candidates will be arranged.
Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.
According to the Norwegian Freedom and Information Act (Offentleglova) information about the applicant may be included in the public applicant list, also in cases where the applicant has requested non-disclosure.
UiO has an agreement for all employees, aiming to secure rights to research results a.o.
Inclusion and diversity are a strength. The University of Oslo has a personnel policy objective of achieving a balanced gender composition. Furthermore, we want employees with diverse professional expertise, life experience and perspectives.
If there are qualified applicants with disabilities, employment gaps or immigrant background, we will invite at least one applicant from each of these categories to an interview.
For further information about the position please contact:
- Prof. Amir Taherkordi, e-mail: firstname.lastname@example.org, Prof. Marin Giese, e-mail: email@example.com or
- Dr. Goulnoush Abbas, e-mail:firstname.lastname@example.org
For questions regarding Jobbnorge, please contact HR Adviser Therese Ringvold, phone: +47 228 51606 e-mail: email@example.com
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