Ledig stilling på Universitetet i Oslo

Blindern og Urbygningen (Foto: Wikimedia og Colourbox)
Blindern og Urbygningen (Foto: Wikimedia og Colourbox)

Postdoctoral Research Fellow in Machine Learning

Deadline: 29.05.2022

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 research at the Department of Physics covers a broad range of subfields within physics and technology: From space research to medical physics. A good proportion of the research is interdisciplinary, and conducted in close cooperation with collaborators in Norway and abroad.

Education and teaching are other essential activities. We offer a broad range of courses, and the Department is involved in several study programmes at bachelor’s and master’s level. Some of the best lecturers in Norway are amongst our employees, and we are proud of our prizewinning teaching and learning environment. The Department has 200 employees, of which 50 are permanent scientific positions. On a yearly basis 20 students complete their Ph.D. and 50 finish their M.Sc. degree.

Job description

A three-year postdoctoral research fellowship in machine learning is available at The Department of Physics.

We are looking for a highly motivated research scientist to work on the project Societal and environmental determinants of brain and cognition. Starting date as soon as possible.

No one can be appointed for more than one Postdoctoral Research Fellowship at the University of Oslo.

More about the position

About the project:

At the University of Oslo, we are starting a new exciting project in the intersection between social science and natural science, funded by the UiO:Lifescience initiative: Societal and environmental determinants of brain and cognition (AHeadForLife) - UiO:Life Science.

The primary objective of the project is to uncover how interactions between the immediate environment, larger societal factors and genes shape brain and cognitive function across the lifespan. We will research the mechanisms that link genes, social outcome and cognition, study the timing, nature and determinants of the relationships between genes, brain, cognition and social outcomes such as socioeconomic status, and use machine learning to describe the relationships between the brain and social outcome variables.

The project evolved in response to a strong joint interest of PIs from diverse fields to understand factors important for brain structure and cognitive function; psychology (Kristine B Walhovd; Anders M Fjell), economics (Ole Røgeberg), sociology (Torkild Hovde Lyngstad), genetics (Yunpeng Wang, Jennifer Harris), biostatistics (Øystein Sørensen) and physics (Atle Bjørnerud).

For this we are seeking four excellent candidates with different scientific backgrounds:

  • PhD: Hired at Department of psychology (the current position)
  • Post doc 1: Hired at Department of sociology and Human geography
  • Post doc 2: Hired at Department of psychology.
  • Post doc position 3: Hired at Department of physics.

Although the candidates formally will be hired at different UiO departments, we will arrange for partly joint office spaces and locales for physical interaction. We are therefore especially interested in candidates who want to work in an interdisciplinary and international environment. We will have bi-weekly meetings with all candidates and project partners to ensure integration across disciplines. Joint supervision from more than one PI will be offered.

This position will formally be at the Department of Physics at UiO, but closely associated with Unit for Computational Radiology and Artificial Intelligence (CRAI: OUH - MR imaging and analysis group (ous-research.no), in the Division for Radiology and Nuclear Medicine at Oslo University Hospital, as well as Center for Lifespan Changes in Brain and Cognition (LCBC) at UiO (www.oslobrains.no). CRAI is a research hub for the advanced computational methods and artificial intelligence in radiology. The unit was established in 2019 in response to the increasing radiology production demands and holds a varied portfolio of projects that uses artificial intelligence techniques at its core. CRAI consists of a motivated and dedicated group of individuals with a mixed background, including machine learning-engineers, medical physicists, medical doctors, and Masters- and PhD students with varied backgrounds. The main goal at CRAI is to build, deploy and maintain machine learning models by developing solid systems that can serve clinicians through augmented decision support and automated diagnostics. The goal of LCBC is to understand brain and cognitive changes and how to optimize them through the entire lifespan. LCBC is an active multidisciplinary research center, with a staff of ≈25 full-time positions, covering psychology, informatics, biostatistics, genetics and physics.

Job description:

The main task is to develop, implement, and test machine learning algorithms applied to magnetic resonance images of the brain to detect brain correlates of different cognitive functions and social variables such as socio-economic status. The project is interdisciplinary, and the candidate will be expected to participate in all activities.

The main purpose of a postdoctoral fellowship is to provide the candidates with enhanced skills to pursue a scientific top position within or beyond academia. To promote a strategic career path, all postdoctoral research fellows are required to submit a professional development plan no later than one month after commencement of the postdoctoral period.

Qualification requirements

The Faculty of Mathematics and Natural Sciences has a strategic ambition is 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.

Required qualifications:

  • Applicants must hold a degree equivalent to a Norwegian doctoral degree in computer science, biostatistics, medical physics, mathematics or similar. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are eligible for appointment.
  • Strong programming skills.
  • Experience with machine learning methods, particularly deep learning.

Other preferred qualifications include:

  • Domain experience in medical image analysis with focus on MRIs of the brain, will constitute an advantage, but is not required.

In the assessment, the main emphasis will be on the applicant's potential as a researcher as shown in the application CV. In addition, consideration is given to professional experience and other activities that are considered important. Finally, personal suitability and compliance within the research group is considered essential. CV content must be documented with diplomas, testimonials and complete publication list.

Personal skills:

  • Good collaboration skills
  • Be able to take responsibility and work independently
  • Team spirit

Language requirements:

  • Fluent oral and written communication skills in English.

We offer

  • Salary NOK 574 700 – 615 800 per annum depending on qualifications in position as Postdoctoral Research Fellowship (position code 1352)
  • A collaborative, pleasant and supporting working environment
  • The opportunity to work with world-leading researchers within different disciplines
  • Flat hierarchy
  • An opportunity to work with big real-world health data
  • Opportunity to create individual research portfolio
  • International collaboration
  • Attractive welfare benefits and a generous pension agreement
  • We have established collaborations with multiple international institutions, and the position will open up for research stays at collaborating institutions.
  • 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 and PhD diploma
  • Transcripts of grades/records
  • Letters of recommendation
  • Documentation of English proficiency
  • List of publications and academic work that the applicant wishes to be considered by the evaluation committee
  • Names and contact details of 2-3 references (name, relation to candidate, e-mail and telephone number)

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.

Formal regulations

Please see the guidelines and regulations for appointments to Postdoctoral fellowships at the University of Oslo.

According to the Norwegian Freedom of 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.

The University of Oslo has an agreement for all employees, aiming to secure rights to research results a.o.

If an applicant has applied for and been granted funding for a research stay abroad while being employed as a Postdoctoral Research Fellow, the employment will be prolonged with the equivalent time as the research stay, but for no longer than twelve months (thus extending the employment to a maximum of four years).

The University of Oslo aims to achieve a balanced gender composition in the workforce and to recruit people with ethnic minority backgrounds.

Contact information

For further information please contact: Professor Atle Bjørnerud, e-mail: [email protected], Telephone: +47 97539499

For questions regarding the recruitment system, please contact HR Adviser Elin Thoresen, e-mail: [email protected].

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