PhD Research Fellow in Deep learning on image data

About the position

Two (2) positions as PhD Research Fellow in machine learning available at the Department for Informatics with the research group Digital Signal Processing and Image Analysis  (https://www.mn.uio.no/ifi/english/research/groups/dsb/index.html) as part of  Visual Intelligence  (http://visual-intelligence.no), Norway’s leading research centre in deep learning for image analysis.
No one can be appointed for more than one PhD Research Fellowship period at the University of Oslo. Starting date no later than October 1, 2024.

The fellowship period is three (3) years.

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.

Knowledge development in a changing world – Science and technology towards 2030.

The Faculty of Mathematics and Natural Sciences

Job description

Two phd positions are open. They are both focused on deep learning for images. Position 1 focuses on medical ultrasound images. Position 2 focuses on image data for monitoring marine ecosystems.  You must indicate in you application if you apply for both projects, or if you apply only for one of the projects. State project 1 for medical images, and project 2 for marine images. We encourage you to apply for both projects. 

Position 1: medical imaging 

You are keen on contributing to new advances in deep learning methodology for cardiac ultrasound imaging. Deep learning methods for cardiac ultrasound can e.g. be used for automatic measurements from image sequences, to assess im-age quality, or take benefits of recent research results in foundational neural models, where models learn from large unlabelled image datasets, but also on additional data like clinical reports or electronic health records. The work will be done in collaboration with GE Healthcare and their research center in Oslo. 

You will focus on challenges related to self-supervised learning, and combine this with either modelling knowledge, incorporate reliability/uncertainty, and/or explainable models. 

Position 2: marine imaging

You are keen on contributing to new advances in deep learning methodology for monitoring marine ecosystems. This can be data collected about the marine environment from e.g., satellites, sonar images, or underwater video from AUVs. The research will be done in cooperation with the Institute of Marine Research. 

The core of the position will be development of new deep learning methods for segmentation/classification of data with limited and weak labels and imbalanced data sets. You can also focus on challenges related to modelling prior knowledge, incorporate uncertainty, or methods with improved explainability. 

Common for both positions:

Your interests are in neural networks research. You have a big motivation to both contribute to new methods in neural networks, and develop models suited to the particular application.

The positions are in the Digital Signal Processing and Image Analysis Group, Section for Machine Learning, Department of Informatics. For more information about the position, see https://www.visual-intelligence.no/about/open-positions . You will be part of Visual Intelligence and the DSB group. We expect that you will engage in collaborative research with other members of the centre and the research group. You will collaborate with user partners within Visual Intelligence, to contribute to the centre’s seminars, to collaborate across innovations areas within the centre, and to seek collaboration between the research partners within the centre. You will be part of a network of young researchers in deep learning in the Visual Intelligence Graduate School https://www.visualintelligence.no/about/vigs 

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.

Required qualifications:

• Master’s degree or equivalent preferably in machine learning or equivalent fields. A background in computer science/statistics/applied mathematics/electrical engineering can also be considered given that the candidate has formal competence in machine learning and/or image analysis/computer vision.
• A solid documented background in machine learning, mathematics, linear algebra, and/or statistics. 
• Documented knowledge and experience in Python programming.
• Foreign completed degrees (M.Sc.-level) must corresponding to a minimum of four years in the Norwegian educational system
• Fluent oral and written communication skills in English

Desired qualifications:

• Experience with frameworks like TensorFlow or PyTorch

Candidates without a master’s degree have until 30 June 2024 to complete the final exam.

Grade requirements:
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 educa-tional system
• English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements:

https://www.mn.uio.no/english/research/phd/regulations/regulations.html#toc8 

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: 

http://www.uio.no/english/research/phd/
 
http://www.mn.uio.no/english/research/phd/

Personal skills

• Good analytical skills  
• Dedication to work with important applications 
• Ability to lead and conduct research in a collaborative environment  
• Ability to work independently as well as in multidisciplinary teams 
• Ability to give and receive constructive scientific criticism 

We offer

• Salary NOK 532 200 – 575 400 per year depending on qualifications and seniority 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
• 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 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.

Contact information

For further information please contact Professor Anne Solberg, phone: +47 228 52435, e-mail: anne@ifi.uio.no, Associate Professor Adín Ramírez Rivera, phone: +47 228 40818, e-mail: adinr@uio.no, or Associate Professor Ali Ramezani-Kebrya, phone +47 22852433, e-mail: ali@ifi.uio.no.

For questions regarding Jobbnorge, please contact HR Adviser Therese Ringvold,  e-mail: therese.ringvold@mn.uio.no

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 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.

 

Deadline: 2024-02-29 at 23:59
Unit: Engineering/it

Read the job description at the university homepage or apply.