PhD Research Fellow in Machine Learning for Cognitive Neuroscience

Adín Ramírez Rivera; Oslo; On-site; NOK 551,000 - 595,000; Full time

Benefits offered by this job

Welfare schemes

Career development

Salary in PhD role

Oslo living

Job summary

The University of Oslo invites applications for a PhD Research Fellow in Machine Learning and Applied Cognitive Neuroscience within the Digital Signal Processing and Image Analysis group.

The three-year fellowship may be extended to four years for teaching and research duties, with a latest start date of December 31, 2026.

Qualifications

• Master's degree in computer science, physics, mathematics, engineering, data science or related fields
• Proficiency in scientific programming (e.g., Python)
• Proficiency in deep learning frameworks (e.g., PyTorch)
• Strong background in machine learning, mathematics, linear algebra and statistics
• Fluent oral and written English proficiency
• Candidates without a master's degree may apply if they are near completion by Sept 30, 2026

Responsibilities

• Develop ML models and frameworks for time series analysis to study neural encoding
• Collaborate across DS B, IFI and Cognitive Neurophysiology groups
• Apply transformer architectures to rodent and human neural data
• Contribute to publications and dissemination of findings

Skills

Machine learning

Time series

Python

PyTorch

English

Education

Master's degree

Job description

About the position

Position as PhD Research Fellow in Machine Learning and Applied Cognitive Neuroscience available at the Department of Informatics.

The fellowship period is three years.

Depending on the candidate and the teaching needs of the department, the fellowship period can be extended either for compulsory work consisting of e.g., teaching and supervision duties and research assistance up to four years. Starting date no later than December 31, 2026.

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

The position is placed in 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 seven full-time and five adjunct positions. We perform research over a wide range of applications in image analysis and machine learning, as well as in digital signal processing and acoustic imaging. There are about 20 Postdocs and PhD research fellows in the group with financing from a variety of national and international funding agencies, as well as from industry.

Job description

We are seeking an ambitious candidate to develop Machine Learning models and frameworks for time series analysis, aimed at understanding how the human brain encodes information.

This cross-disciplinary project is a high-level collaboration between the Digital Signal Processing Group (DSB), at the Section for Machine Learning (IFI), and the Group for Cognitive Neurophysiology (Medical Faculty). The team has research links with Bradley Voytek at the Halıcıoğlu Data Science Institute (University of California San Diego, USA). By bridging experimental neurophysiology with advanced algorithmic design, we aim to significantly enhance the understanding of high-dimensional neural activity patterns.

The successful candidate will work with open available datasets obtained in rodents and unique datasets of neural activity. Your primary focus will be to design new learning frameworks and neural network architectures to advance our fundamental understanding of how the human brain forms perception and memories. In detail, you will use transformer architectures to analyze time series of local field potentials recorded in rodents and compare performance to time series of action potentials recorded in the same animals (the state of the art); apply and interpret the architecture to local field potential data recorded in humans who have seen a vast number of images from the CoCo-database ( https://cocodataset.org ); and apply and interpret the architecture to local field potential data recorded in humans who have seen movies.

The data for the project is already collected and available. Project leaders are Adin Ramirez Rivera (DSB, IFI) and Jørgen Sugar (Medical Faculty).

Whatskillsareimportantinthisrole?

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 mathematics, electrical engineering, cybernetics, data science, computational science, neuroscience or related fields
• For applicants with a foreign completed degree (master level), it must be equivalent to a master in the Norwegian educational system
• Documented proficiency in scientific programming (e.g., Python)
• Documented proficiency in deep learning frameworks (e.g., PyTorch)
• Documented background in machine learning, mathematics, linear algebra, and statistics
• Fluent oral and written communication skills in English

Desired qualifications:

• Experience with transformer models and attention mechanisms
• Strong background in probabilistic machine learning
• Proven track record in time-series analysis and modeling, signal processing, medical domain, and/or related fields
• Strong writing skills

Candidates without a master’s degree have until September 30, 2026 to complete the final exam.

Language requirement:

• Good oral and written communication skills in English
• 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

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

The purpose of the fellowship is research training leading to the successful completion of a PhD degree. For more information see:
http://www.mn.uio.no/english/research/phd/

All candidates and projects will have to undergo a check versus national export, sanctions and security regulations. Candidates may be excluded based on these checks. Primary checkpoints are the Export Control regulation, the Sanctions regulation, and the national security regulation.

What are we looking for in you?

Personal skills:

• Ability to work both independently and as part of a team
• Ability to work precisely and in a structured manner, while adapting to new tasks
• Excellent communication and collaboration skills
• Positive attitude and ability to handle hectic periods
• You are a person who prefers being present at work and actively contributes to the professional and social environment you are a part of

Employment in the position is based on a comprehensive assessment of all qualification requirements applicable to the position, including personal qualifications.

We can offer you

• A pleasant and stimulating work environment
• Good welfare schemes
• Opportunity of up to 1.5 hours a week of exercise during working hours
• A workplace with good development and career opportunities
• Career development programmes
• Membership in the Statens Pensjonskasse, which is one of Norway's best pension schemes with beneficial mortgages and good insurance schemes
• Oslo’s family-friendly surroundings with their rich opportunities for culture and outdoor activities
• Salary in position as PhD Research Fellow, position code 1017 in salary range NOK from 550 800 - 595 000, depending on competence and experience. From the salary, 2 percent is deducted in statutory contributions to the State Pension Fund

We need different perspectives in our work

UiO is an open and internationally oriented comprehensive university that strives to be an inclusive and diverse workplace and academic environment. You can read more about UiO’s work on equality, inclusion, and diversity at uio.no .

We fulfill our mission most effectively when we draw upon our variety of experiences, backgrounds, and perspectives. We are looking for great colleagues, could you be the next one?

We will do our best to accommodate your needs. Relevant adjustments may include modifications to working hours, task adaptations, digital, technical, or physical adjustments, or other practical measures.

If you have an immigrant background, a disability, or CV gaps (Norwegian), we encourage you to indicate this in the job application portal. We always invite at least one qualified candidate from each group for an interview. In this context, disability is defined as an applicant who identifies as having a disability that requires workplace or employment-related accommodations. For more details about the requirements, please refer to the Employer portal (Norwegian).

The selections made in the job application portal are used for anonymized statistics that all state employers include in their annual reports. More information about gender equality initiatives at UiO can be found here .

General information

The best qualified candidates will invited for interviews. Applicant lists can be published in accordance with Norwegian Freedom of Information Act § 25 . When you apply for a position with us, your name will appear on the public applicant list. It is possible to request to be excluded from this list. You must justify why you want an exemption from publication and we will then decide whether we can grant your request. If we can't, you will hear from us.

Please refer to Regulations for the Act on universities and colleges chapter 3 (Norwegian), Guidelines concerning appointment to post doctoraland research posts at UiO (Norwegian) and Regulations for the degree of Philosophiae Doctor (PhD) at the University of Oslo .

The University of Oslo has a transfer agreement with all employees that is intended to secure the rights to all research results etc.