OsloMet – Oslo Metropolitan University is Norway’s third largest university, with nearly 22,000 students and 2,200 employees. Through the students we educate and the research we produce, the university has a direct impact on society, both in Norway and beyond. The university has two campuses, one in central Oslo and another a short distance from the city in the municipality of Lillestrøm. OsloMet is home to some of Norway’s largest and oldest educational programmes, including degree programmes in nursing, engineering and teacher education. The university is also a hub of research and technological innovation aimed at strengthening and sustaining the Norwegian welfare state.
The Faculty of Technology, Art and Design (TKD) offers higher education and research and development (R&D) activities within technical subjects, arts and design. The Faculty has approximately 4.000 students and 400 staff members and is situated at Pilestredet Campus in downtown Oslo and at Kjeller Campus in Viken.
The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department are pursuing research in a wide range of areas including computer science, the natural sciences, and innovation and management. Both students and researchers are also involved in an increasing number of interdisciplinary initiatives across the university.
Associate Professor in Applied Data Science
The OsloMet Ai Lab organizes training and develops basic and applied research in machine learning, data science, artificial intelligence and unconventional computing. Health, security, data journalism, energy, sport, mobility, marine robotics, arts, sustainability and trustworthiness are currently the focus of applied AI research. For basic research, the lab emphasizes different fields namely artificial life, quantum computing, reinforcement learning, stochastic processes and genetic algorithms. More information about the lab can be found in the following link https://www.oslomet.no/om/tkd/it/ai-lab
The Computer Science Department has an open permanent position for an Associate Professor in Applied Data Science starting in 2023. We seek a candidate with a background in higher education, research, innovation, and science communication. The ideal candidate will be a seasoned expert in the field of data science, particularly in the application of data analysis in the areas of journalism, media, health, and text analysis. The successful applicant should have demonstrated research proficiency in areas such as applied statistics, machine learning, or artificial intelligence.
Your main duties and areas of responsibility will be to
- teach courses at bachelor, master and PhD level, within topics relevant for the Department of Computer Science. This includes teaching, assessment, and development of existing/new courses.
- supervise, advise, and mentor at the bachelor, master and PhD level.
- plan, develop and deliver courses within the realm of lifelong learning education
- conduct research and write proposals to secure research funding from external sources
- communicate and disseminate research results both in academic settings and for the general public
- actively contribute to the development of high-quality of research and education at the Department of Computer Science and OsloMet as a whole
- perform administrative tasks related to educational, research, innovation and scientific communication activities
Qualification requirements
- doctoral degree in a STEM (science technology engineering and mathematics) subject.
- documented research and publications within applied statistics, machine learning, or artificial intelligence
- documented expertise with Python at a master or Ph.D. Level
- written and oral proficiency in Norwegian or another Scandinavian language, and English
Applicants who do not have adequate proficiency in Norwegian or another Scandinavian language, shall be offered Norwegian courses, and must acquire Norwegian skills corresponding to at least level B2 within three years of appointment.
The applicant must document relevant educational competence in accordance with OsloMet’s Guidelines for the assessment of educational competence at OsloMet.
General criteria for appointments to academic positions are covered by the Regulations for appointment and promotion to academic posts.
Emphasis will be placed on
- passion for teaching and supervision at all levels
- teaching experience, good pedagogical abilities, and the ability to motivate and inspire students
- flexibility and ability to adapt the teaching to the needs of OsloMet and the faculty,
- proven experience with data science within the fields of journalism, health and/or text analysis
- good oral and written abilities in Norwegian, or another Scandinavian language is an advantage
- experience with communication to non-academic audiences,
- practical experience or industry experience from applied artificial intelligence, data science, or related fields
- experience with and interest in technology transfer, innovation, and patents
- proven experience with interdisciplinary projects is an advantage
Personal qualities required for the position
- the ability to motivate and inspire students and colleagues
- good cooperation and communication skills
- inquisitiveness, and a keenness to develop as a researcher and an educator
- flexibility and ability to work interdisciplinary and collaborate with people with diverse backgrounds
- the ability to build communities and networks, establish research projects, and demonstrate fresh thinking and innovation
Emphasis will be placed on personal suitability.
OsloMet will test the candidates’ educational qualifications in connection with interviews.
It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active endeavors to further develop OsloMet as an inclusive workplace and to make adaptations to the workplace where required. You are also welcomed to apply for a position with us if you have had periods where you have not been in employment, education or training.
Application process
You will be assessed by an Expert Committee. Please upload the following documents with the application within the application deadline:
- application letter
- CV (including teaching and supervision experience)
- name and contact information of at least three references
- Complete list of publications
- copies of certificates/diplomas (including formal education in pedagogics, if applicable)
- up to ten full-text scientific articles, submitted together with a table of contents and a short introduction highlighting the relevance of the article to the profile of the position and a detailed description of the contribution to the article by the applicant
- documentation of educational competence including a profiling document. For applicants who cannot document competencies within teaching in higher education have to develop this within two years from accession. OsloMet offers courses in teaching and learning in higher education which covers this requirement.
- a text (up to 2 pages) outlining your relevant pedagogical experience and plans for pedagogical activity and development in the position (“teaching statement”) and the pedagogical stance of the applicant. If relevant, this overview should also include recent student-evaluations.
- a text (up to 2 pages) outlining your relevant research and plans for research activity in the position (“research statement”). This overview should include an overview of existing projects and research collaborators.
- other relevant documentation
We only consider applications submitted through our electronic recruitment system, and all documents must be uploaded for your application to be considered. The documents must be in a Scandinavian language or English. Translations must be authorized, and you will be asked to present originals if you are invited for an interview. OsloMet verifies documents to give candidates a proper evaluation and ensure fair competition. Incomplete applications will not be considered.
Before the application papers are forwarded to the expert committee, all applications will be reviewed by the faculty. Applications from applicants who do not meet the formal qualification requirements will not be forwarded for assessment.
If you have documents that cannot be uploaded electronically, please contact hrtkd@oslomet.no
We offer
- exciting job tasks at Norway’s third largest university
- participation in research groups and a creative and inspiring academic community
- opportunities for academic development
- time for profession-oriented research and development work
- good welfare schemes and a wide range of sports and cultural offers
- loan and pension arrangements with the Norwegian Public Service Pension Fund
The salary for the position is in accordance with the Basic Collective Agreement for state employees and OsloMets pay policy for, corresponding to NOK 553 500 – 714 000 per year. From the salary, 2% will be deducted in pension contributions for the Norwegian Public Service Pension Fund (SPK). A higher salary may be considered for particularly well-qualified applicants.
The engagement is to be made in accordance with the regulations in force concerning State Employees and Civil Servants, and the acts relating to Control of the Export of Strategic Goods, Services and Technology.
Other information
If you would like more information about the position about the position, feel free to contact:
- Head of Department Laurence Habib, +47 67 23 86 57, e-mail laurence@oslomet.no
- Head of Group Gustavo Mello, +47 411 51 686, e-mail: gustavom@oslomet.no
Deadline for applications: 23.04.2023
Ref. no: 23/01533
OsloMet is a Charter & Code certified institution by the EU Commisson holding the right to use the logo HR Excellence in Research (HRS4R). OsloMet is a member of the EURAXESS network supporting a positive work environment for researchers in motion. OsloMet has signed The Declaration on Research Assessment (DORA). DORA recognizes the need to improve the ways in which the outputs of scholarly research are evaluated.
