PhD Research Fellow in Probabilistic Machine Learning

Engineering/it

PhD Research Fellow in Probabilistic Machine Learning

About the position

Position as PhD Research Fellow in Probabilistic Machine Learning available at the Digital Signal Processing and Image Analysis group (DSB), Section for Machine Learning, Department of Informatics at the University of Oslo. 

The DSB research group has six full-time and four adjunct positions. We perform research over a wide range of applications in image analysis and deep learning, as well as in digital signal processing and acoustic imaging. There are about 20 Postdocs and PhD students in the group with financing from a variety of national and international funding agencies, as well as from industry.     

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

We are in search of a committed PhD candidate to become part of our team, focusing on self-supervised learning problems and probabilistic machine learning. The candidate will advance our understanding of latent representations and their distinctive spaces, tailoring them with properties that are advantageous for tasks involving visual data. Our aim is to devise novel algorithms capable of recognizing and interpreting unknown patterns within such data. Furthermore, we intend to refine self-supervised methods that excel in learning from limited data, applying them to a broad spectrum of challenges.

The ideal candidate will have strong analytical skills, show proficiency in writing code and developing algorithms, demonstrate meticulous attention to detail, and exhibit a strong curiosity to create interpretable statistical models. A significant part of this role will include experimentation with probabilistic machine learning techniques to generate robust and reliable data representations. We have a specific interest in candidates experienced in areas related to visual data, such as medical imaging, seismic data, time series data, and remote sensing data.

We are a forward-thinking group that welcomes diversity in thinking and encourages theoretical and practical explorations beyond the areas mentioned. We anchor this role in unfolding creative, innovative solutions and welcome the suc-cessful candidate to bring in fresh ideas and perspectives.

This position offers an open platform for intellectual dialogue and discovery. If you are passionate about leveraging self-supervised learning to push the bounda-ries in machine learning, we invite you to apply. Our dynamic team will support your innovative ideas and provide opportunities for you to shape the future direc-tion of our research.

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 in computer science, physics, applied mathe-matics, electrical engineering, cybernetics, data science, computational science, or related fields. Foreign completed degrees (M.Sc.-level) must correspond to a minimum of four years in the Norwegian educational system.
  • Proficiency in scientific programming (e.g., Python).
  • Proficiency in deep learning frameworks (e.g., Pytorch).
  • Strong skills and documented background in machine learning, mathematics, linear algebra, and statistics.
  • Willingness to be part of a team and to share knowledge and skills.
  • Ability to communicate science. 
  • Strong writing skills.
  • Fluent oral and written communication skills in English

Desired qualifications:

  • Experience in probabilistic deep learning
  • Experience in computer vision or working with visual data

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

We look for an enthusiastic self-motivated candidate who can work efficiently both in group and individually. We expect :

  • A passion for computer vision, machine learning, scientific programming, and problem solving.
  • Ability to carry out and complete major tasks.
  • Collaborative skills and willingness to share knowledge, information and to support others in the pursuit of team goals.

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 the following enumerated attachments in PDF format: 

  • Cover letter—statement of motivation and research interests, including a description of the relevance of your MSc in relation to this project as well as the required and desired position qualifications. 
  • CV (summarizing education, positions and academic work—scientific publications).
  • Copies of the original Bachelor and Master’s degree diploma, 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”). Applications submitted through other channels, such as direct e-mail, will not be evaluated. 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 Associate Professor Adín Ramírez Rivera, e-mail: adinr@uio.no, phone +47 228 40818.

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.