OsloMet – Oslo Metropolitan University

Ph.D. fellow position in Deep Learning Techniques for Dementia Risk Assessment - EU Horizon 2020 project AI-Mind

Tallenna suosikiksi Luo Paikkavahti

Tietoja työnantajasta

OsloMet's vision is to deliver knowledge to solve societal challenges. Norway's most urban and 3rd largest university.

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The Department of Computer Science offers three bachelor’s degree programmes, a master’s degree programme, and is part of a cross-departmental PhD program. Academic staff at the department are pursuing research in a wide range of areas including computer science, the natural sciences, and innovation and management. Both students and researchers are also involved in an increasing number of interdisciplinary initiatives across the university.

Job Description

The candidate will be affiliated to the Department of Computer Science, to the OsloMet/SimulaMet AI Lab and to the Center of Research Excellence at OsloMet, NordSTAR, , working within the Horizon 2020 European project AI-Mind on the development of deep learning techniques for extracting discriminative functional brain connectivity features from EEG signals, and prediction of dementia using multimodal data. The AI-Mind project focuses on intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment. OsloMet is leading the development of the AI tools in the AI-Mind project in collaboration with Aalto University.

Context of the AI-Mind project: More than 10 million Europeans show signs of mild cognitive impairment (MCI), a condition intermediate between normal brain ageing and dementia. The evolution of MCI differs from person to person; some remain stable or return to normal, but 50% progress to dementia within five years. Current practice lacks the necessary screening tools to identify those 50% at risk. The patient’s journey typically takes many years of inefficient clinical follow-ups before a conclusive diagnosis is finally reached. AI-Mind will radically shorten this journey to one week through a digital solution that is able to provide a fast and accurate (>95%) prediction for the individual dementia risk. Our AI-Mind platform service can be easily integrated into existing clinical practices and contains two new artificial-intelligence-based tools. The AI-Mind Connector identifies dysfunctional brain networks. The AI-Mind Predictor assesses dementia risk using data from the Connector, advanced cognitive tests, genetic biomarkers and important textual variables. Our aim is to set up a European clinical network that will upload patient data to the AI-Mind European cloud platform. The consortium comprises excellent researchers in neuroscience and computer science, from five clinical centers, who closely collaborate with three SMEs contributing unique technologies, an established data governance body-DNV GL, and Alzheimer Europe. Together, they plan to deliver a medical device of class 2b that can reach TRL7 by the end of the project. AI-Mind represents a major step forward in the risk assessment of dementia.

The Norwegian coordinated AI-Mind project has received substantial funding from the European Union’s Horizon 2020 research and innovation program under Grant Agreement No 964220. AI-Mind is a five-year Research and Innovation Action (RIA) that officially starts in March 2021, with a budget of EUR14 million.

Project overview

Within the AI-Mind project, the candidate will focus on building a Connector will fully automate the identification of early brain network disturbances using deep learning techniques and on developing the AI-Mind Predictor will assess the risk of dementia using Connector data, advanced cognitive tests and genetic biomarkers. The Phd candidate will be collaborating with other Ph.D. candidates from Oslo University Hospital and OsloMet working on the project.  To this end, different deep learning techniques will be tested to analyze EEG data and build accurate biomarkers of brain disorders.

The PhD candidate will be working with the AI-Mind project in collaboration with different teams from Neuroscience across Europe and computer science. A close collaboration with Aalto University (Finland) led by Professor Samuel Kaski is expected. Aalto University is responsible for the counter-part version of the Connector using probabilistic machine learning.

For further details about the project contact:

  • Prof. Anis Yazidi (main supervisor), anis.yazidi@oslomet.no
  • Prof. Pedro Lind, pedro.lind@oslomet.no

The Ph.D. fellowship will be offered for a period of three years (100% position), or alternatively, four years including 25% compulsory work (teaching and supervision activities or research administrative work). The decision on whether a 3 or 4-year position is suitable will be discussed as part of the interview process. The successful applicant should have the goal to complete the Ph.D. program within this time frame and receive a Ph.D.

The position will be available from 01.01.2022.

Qualification requirements

We are looking for candidates that must:

  • Master’s thesis in computer science, electrical engineering or related fields (equivalent to 120 credits) with a grade B or better with a background in an area relevant for the PhD project. Diplomas from Master’s degree must be submitted prior to signing of the contract.
  • be proficient in written and spoken English
  • have knowledge in machine learning techniques
  • have good programming skills especially in Python, or other related programming languages such as R and Matlab

The Ph.D must have approved admission to the Ph.D. program in Engineering Science within 3
months after employment in the position.

Candidates who already hold a PhD in the same or similar field may not apply.

The successful candidate will be expected to participate actively in the AI-Mind research.

It would be an advantage if the candidate

  • is familiar with health research in general and neuroscience research in particular
  • has good knowledge in deep learning
  • has knowledge in modern deep learning architecture
  • has knowledge in explainable AI
  • has knowledge in multimodal classification
  • has knowledge in statistical learning and statistics
  • has an ability to perform interdisciplinary work

Ability to and interest for public dissemination of the research will also be considered an advantage.

Desired personal skills

  • the ability to work systematically and proactively
  • the ability to finish tasks
  • motivation for contribution in the field of research

It is important to OsloMet to reflect the population of our region, and all qualified candidates are welcome to apply. We make active efforts to further develop OsloMet as an inclusive workplace and to adapt the workplace if required. You are also welcome to apply for a position with us if you have experienced periods where you have not been in work, education or training.


In order to be considered for the position you must upload the following documents together with your online application by the final date for the applications:

  • Cover letter, stating your reasons for applying and provide reasons for why you are particularly qualified for this Ph.D. fellowship position.
  • CV and all pages of certificates/diplomas. The certificates/diplomas must include ECTS grades (A– F). Foreign diplomas must be translated into English by the degree-conferring institution. Education taken abroad should preferably be recognised in advance by NOKUT, and a confirmed copy of the letter of recognition should be enclosed.
  • Master's degree/second degree thesis (and any other scholarly work that the expert committee should take into consideration). In case Master is not defended by time of application, the applicant must submit a reference letter from master supervisor confirming the ongoing master activity and planned date of defense. Diplomas from Master’s degree
    must be submitted prior to signing of the contract.
  • List of publications, if relevant.
  • The names and contact details of at least two references.
  • Applicants from countries where English is not the first language must present an official language test report. The following applicants are exempt from the abovementioned language requirements:
    • Applicants from EU/EEA countries.
    • Applicants who have completed one year of university studies in Australia, Canada, Ireland, New Zealand, the UK or USA.
    • Applicants with an International Baccalaureate (IB) diploma.
  • The following tests qualify as such documentation: TOEFL, IELTS, Cambridge Certificate in Advanced English (CAE) or Cambridge Certificate of Proficiency in English (CPE). Minimum scores are:
    • TOEFL: 600 (paper-based test), 92 (Internet-based test).
    • IELTS: 6.5, with no section lower than 5.5 (only Academic IELTS test is accepted).

All the documents must be written in English. Any translations must be authorized by the government. Originals must be presented if you are invited for an interview. OsloMet performs document inspections in order to give you as a candidate a proper evaluation and ensure fair competition.

Please note that incomplete applications will not be considered.

We can offer you

  • An exciting job opportunity at Norway’s third largest and most urban university.
  • Opportunity to be a part of a dynamic professional environment and unique academic network.
  • Beneficial pension arrangements with the Norwegian State Pension Fund.
  • Good employee welfare arrangements.
  • Working location in downtown Oslo with multiple cultural offers.

Practical information about relocation to Oslo and living in Norway.


Salary is set in accordance with the Norwegian State Salary Scale, position code 1017 PhD Fellowship, pay grade 54, NOK 491 200. By law 2% of the salary is deducted as to the Norwegian State Pension Fund.

The position adheres to the Norwegian Government’s policy that the national labour force should to the greatest possible extent reflect the diversity of the population. Therefore, we encourage qualified candidates with immigrant background or reduced functional ability to apply for this position. OsloMet is an IA (Inclusive Workplace) enterprise and operates in compliance with the Norwegian IA agreement.

According to the Norwegian Freedom of Information Act (Offentleglova) your name may be published on the public applicant list even if you have requested non-disclosure. You will in this case be contacted before your name is published.

Please apply electronically to this position by clicking on the button «Click here and apply».

Ref:  21/04465

Deadline for applications: January 30th 2022

Lisätietoa työpaikasta

Ph.D. fellow position in Deep Learning Techniques for Dementia Risk Assessment - EU Horizon 2020 project AI-Mind
Pilestredet 46 Oslo, Norja
Viimeinen hakupäivä
Työpaikan tyyppi
Tallenna suosikiksi Luo Paikkavahti

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Tietoja työnantajasta

OsloMet's vision is to deliver knowledge to solve societal challenges. Norway's most urban and 3rd largest university.

Käy työnantajan sivulla

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