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PhD Research Fellow in Machine Learning

Deadline: 28.02.2023

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 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.

Job description

Position as PhD Research Fellow in Machine Learning available in the Section for Machine Learning, Department of Informatics at the University of Oslo.

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, 2023.

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.

More about the position

This Ph.D. position is focused on the core of deep learning, which involves both designing learning algorithms to deliver deep learning’s promises and understanding deep learning to explain how deep neural networks learn powerful representations when trained by stochastic gradient descent and its variants.

Deep learning faces significant challenges including scalability, robustness and security, privacy, fairness, and interpretability. The data volume for learning and the size of neural networks grows exponentially, e.g, the number of parameters for recent deep language models surpasses hundreds of billions. Beyond scalability, it is known that machine learning models are vulnerable to various adversarial attacks at training and test time.

Regarding the underlying architecture, a fundamental open question is how many parameters are required for a deep neural network to generalize under common deep learning practice with nonsmooth activations. For the emerging self-supervised learning paradigm, it is important to understand how much additional scaling costs we should pay to relax the requirements for labelled data.

The main research challenges for this project include:

  • Develop highly scalable learning algorithms beyond image classification tasks with guarantees on fairness and privacy;
  • Improve robustness by developing a unified framework for addressing adversarial attacks and distributions shifts;
  • Understand and design underlying architecture in particular deep neural networks

This position is funded by the Department of Informatics and is placed with the Digital Signal Processing and Image Analysis (DSB) group who has its offices in the Ole-Johan Dahl Building, close to the Forskningsparken metro and tramway station in Oslo. The DSB research group has about 20 Postdocs and PhD students with funding from a variety of national and international funding agencies, as well as industry. Our research spans a wide range of applications in image analysis and deep learning, as well as in digital signal processing/acoustic imaging.

The candidate is expected to publish research results in major ML venues and has the opportunity to collaborate with the DSB group, Department of Informatics, the Visual Intelligence Center, and our top-notch international collaborators at EPFL, Vector Institute, and the University of Toronto.

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 this fellowship 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 Master’s degree or equivalent in computer science, mathematics, physics, applied mathematics, electrical engineering, cybernetics, data science, computational science, or related field
  • Foreign completed degree (M.Sc.-level) corresponding to a minimum of four years in the Norwegian educational system.
  • Proficiency in scientific programming (Python)
  • Proficiency in deep learning frameworks (Tensorflow or Pytorch)
  • Strong background in machine learning, design and analysis of algorithms, linear algebra, probability, and statistics
  • Willingness to be part of a team and to share knowledge and skills. Ability to communicate science
  • Strong writing skills
  • Spoken and written fluency in English

The following are also desirable:

  • Experience with broader topics in distributed learning and distributed systems, computer vision, learning theory, reinforcement learning, theoretical computer science, game theory, optimization, operation research.
  • Experience in writing papers in top conferences/journals.
  • Efficient coding skills in C or C++.
  • Experience in high performance computing and tooling in Linux.
  • Manuscript writing skills in LaTeX.

Candidates without a Master’s degree have until 30 June, 2023 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 educational system
  • Fluent oral and written communication skills in English

English requirements for applicants from outside of EU/ EEA countries and exemptions from the requirements

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:

Personal skills

  • Passion for machine learning, theory, 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 501 200 – 544 400 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)
  • Copies of the original Bachelor and Master’s degree diploma, transcripts of records
  • 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 submitted to 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.

Applicants will be called in for an interview.

Formal regulations

Please see the guidelines and regulations for appointments to Research Fellowships at the University of Oslo.

No one can be appointed for more than one PhD Research Fellowship period 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 etc.

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:

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

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