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Oslo Metropolitan University is Norway's third largest university with almost 22,000 students and over 2,500 employees. We have campuses in central Oslo and at Romerike. OsloMet educates students and conducts research that contributes to the sustainability of the Norwegian welfare state and the metropolitan region.
The Faculty of Technology, Art and Design (TKD) offers higher education and research and development (R&D) activities within technical subjects, arts and design. The Faculty has approximately 4.000 students and 400 staff members and is situated at Pilestredet Campus in downtown Oslo and at Kjeller Campus in Viken.
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.
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.
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.
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.
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.
We are looking for candidates that must:
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.
Ability to and interest for public dissemination of the research will also be considered an advantage.
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:
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.
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
Type of employment | Stipendiat |
---|---|
Contract type | Full time |
Salary | NOK 491 200 |
Number of positions | 1 |
Full-time equivalent | 100% |
City | Oslo |
County | Oslo |
Country | Norway |
Reference number | 21/04465 |
Contact |
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Published | 22.Dec.2021 |
Last application date | 30.Jan.2022 11:59 PM CET |