Postdoctoral Research Fellow in Statistics or Machine Learning

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Postdoctoral Research Fellow in Statistics or Machine Learning
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Job description

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

The position is financed by UiO’s interdisciplinary strategic area UiO: Life Science   as part of a convergence environment. Convergence environments are interdisciplinary research groups that will aim to solve grand challenges related to health and environment.

We are looking for a highly motivated research scientist to work on the project Societal and environmental determinants of brain and cognition. Starting date preferably before May 1, 2023.

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).

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

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More about the position

About the project:

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 advanced statistical methods and 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 

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 (current position).

About the position:

The 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:

Job description: The main task is to develop, implement, and test advanced statistical models, including machine learning algorithms, on magnetic resonance images of the brain, genetic information and other complex data. The project is interdisciplinary, and the candidate will be expected to participate in all activities. A high degree of collaboration with other researchers is expected, both when it comes to application as well as development of new methods:

Applied data science:

• Have a genuine interest in analyzing data, and be a discussion partner and adviser for ongoing research projects at CRAI and LCBC.
• Set up and run advanced statistical models for ongoing research projects, and contribute to the interpretation of the results. This may involve generalized additive mixed models, longitudinal data analysis, latent variable modeling, and spatiotemporal mixed models.
• Effectively use UiO’s high performance computing cluster (Colossus, TSD). Balance complexity of statistical models against computational scalability.
• Data wrangling, including combining large and heterogeneous datasets containing different variable types, e.g., cognitive tests, brain characteristics derived from MRI or EEG, demographic variables, and genetics.
• Data visualization, being able to create appealing and informative graphics summarizing key features of data or statistical models.

Methods development:

This will include the need for improvement of both methods and software. The successful candidate will use this as an inspiration in their own work on development of statistical methods. The candidate will have a large degree of freedom with regards to the directions this will take, but we here mention some examples of potential venues:

• Our data often have an overrepresentation of certain demographic groups. How do we correct parameters estimates for this sampling bias?
• In sleep experiments, participants wear electrodes a whole night, yielding densely sampled time series. Can the characteristics of the signals (e.g., alignment of waves at different frequency spectra) explain how well memories are formed during sleep?
• In typical analysis of MRI data, raw images are first run through a segmentation algorithm, estimating thickness, area, and volume of a number of brain regions. In subsequent analyses, these variables are treated as data, and their uncertainty is ignored. Modern segmentation methods are however often Bayesian, and are able to deliver posterior distributions. How can we most effectively utilize this posterior information to ensure that uncertainty is properly propagated into the statistical models used in subsequent analysis steps?
• We have multivariate longitudinal data, and it is of high interest to use these to understand the timing of events (e.g., whether change in a certain brain area occurs prior to memory decline?). Unfortunately, the nonlinear nature of lifespan brain development makes it hard to use existing tools for causal mediator analysis. Is it possible to extend current methods to incorporate nonlinear effects, e.g., with smoothing splines?

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 advanced statistics and/ or machine learning methods, particularly deep learning
• A track record of relevant publications

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.

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.

We offer

• Salary NOK 584 700 – 636 700 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

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.

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

or Professor Anders M Fjell, e-mail: [email protected]

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

About the University of 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.

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