Researcher in machine learning modeling of human physiological models

About the position

Position as Researcher available at the Center for Computing in Science Education (CCSE) and the Techwell center, Department of Physics, Faculty of Mathematics and Natural Sciences, University of Oslo.

The position is for a period of 2 years. 

Starting date no later than 01.03.2025.

Knowledge development in a changing world - Science and technology towards 2030

The Faculty of Mathematics and Natural Sciences

Job description/project description:

The researcher position will be associated with the Maxsense project, which is financed by the Norwegian Research Council as a collaboration between the University of Oslo, SINTEF and several industry partners. The position is at the University of Oslo, in the Department of Physics and the Center for Computing in Science Education, which is a Norwegian Center for Excellence. The successful candidate will work in the Department of Physics and collaborate with the project group at SINTEF. 

The goal of the Maxsense project is to develop methods, techniques and the research basis for a portable AI-based, marker-free 3D modelling system to generate personalized musculoskeletal models. We utilize recent advances in programming tools for hybrid physics-AI problems and combine them with fundamental knowledge about human physiology to create personalized models (or avatars) from observations of humans in motion. Combining physiological models with data from sensors on and around the user, we get high-value data that can be used to improve training, work situations or product design. 

The researcher is expected to contribute to the development of machine learning methods for the development of musculoskeletal models with emphasis on (i) curriculum learning based approaches to control complex motions of physiological models in physical environments such as the motion of the whole body during sitting, walking, running or performing sports; or (ii) generative machine-learning models for physiologically realistic avatar construction from image or point-cloud data. 

Qualification requirements:

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 degree equivalent to a Norwegian doctoral degree in physics, mathematics, biomechanics, AI or machine learning. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defense are eligible for appointment
• Fluent oral and written communication skills in English 
• Documented experience with relevant machine learning methods

The following qualifications will count in the assessment of the applicants:

• Documented experience with parametric human body models (e.g. SMPL, STAR or GHUM) or musculoskeletal modelling (e.g. OpenSim or MyoSuit) or 3D computer vision 
• Experience with deep learning and optimization tools 
• Interest in the biomechanics of human motion

Personal skills:

• Strong collaborative and communication skills
• High personal motivation for research
• A commitment to work towards the research project’s common goals
• Ability to be focused, work independently and collaborate

We offer:

• Salary NOK minimum 575 400 – 692 400 per annum depending on qualifications in position as Researcher (position code 1109)
• Attractive welfare benefits and a generous pension agreement
• Professionally stimulating working environment
• Vibrant international academic environment
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities

The application must include:

• Cover letter (statement of motivation, summarizing scientific work and research interest)
• CV (summarizing education, positions, pedagogical experience, administrative experience and other qualifying activity)
• Copies of educational certificates, academic transcript of records and letters of recommendation
• A complete list of publications and up to 5 academic works 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).

In assessing the applications, special emphasis will be placed on the documented, academic qualifications, as well as the candidates motivation and personal suitability. Interviews with the best qualified candidates will be arranged.

It is expected that the successful candidate will be able to complete the project in the course of the period of employment.

Formal regulations:

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.

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 persons:

For further information about the position, please contact Dr. Øyvind Gløersen Haga, Oyvind.Gloersen@sintef.no, or Professor Anders Malthe-Sørenssen, malthe@fys.uio.no

For technical questions regarding the recruitment system please contact: HR adviser Elin Thoresen, elin.thoresen@mn.uio.no