Postdoctoral Research Fellow in Deep Learning Techniques for Dementia Risk Assessment - Hiring in process/Finished, not possible to apply

The Department of Computer Science has a vacancy for a Postdoctoral Research Fellow in the field of Artificial Intelligence (AI) is offered for the period of 2 years, with a possible extension. The position will be available from January 2022.

The Postdoctoral Fellow will be affiliated to the Department of Computer Science, and to the OsloMet/SimulaMet AI Lab, 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.

Read more about the Faculty and Department here: Department of Computer Science - OsloMet

Read more about our Research Groups here: Research and development - OsloMet

Project overview

Within the AI-Mind project, the Postdoctoral Fellow 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. To this end, different deep learning techniques will be tested to analyze EEG data and build accurate biomarkers of brain disorders.

The Postdoctoral Fellow 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.

Your duties and responsibilities will be 

• Research on AI applied to Neuroscience data
• Conduct experiments using machine learning techniques
• Disseminate the projects results and outcome through appropriate channels
• Conduct administrative tasks as a project partner

Qualification requirements 

• PhD degree in Computer Science or other related fields
• good oral and written presentation skills in English are required
• have expertise in machine learning techniques and especially deep learning techniques

General criteria for appointments to academic positions are covered by the Forskrift om ansettelsesvilkår for stillinger som postdoktor, stipendiat, vitenskapelig assistent og spesialistkandidat

The following will be emphasized

• familiar with health research in general and neuroscience research in particular
• expertise in in deep learning
• documented research in multimodal classification
• an ability to work interdisciplinary
• experience with supervising graduate students

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 welcomed to apply for a position with us if you have experienced periods where you have not been in work, education or training.

Application process

If you would like to apply for the position you must do so electronically through our recruitment system.

You will be assessed by an Expert Committee. You must upload the following documents with the application within the application deadline:

• Application letter
• A plan of up to two pages including references outlining how you propose to conduct this post-doctoral project main research ideas, motivation and background
• CV (including the name and contact information of at least two references)
• Copies of certificates/diplomas
• Complete publication list
• Up to ten full-text scientific articles, submitted together with a table of contents and a short introduction highlighting the relevance of the article to the profile of the position and a detailed description of the contribution to the article by the applicant
• a summary of your PhD thesis

We only process applications sent via our electronic recruitment system and all documents must be uploaded for your application to be processed. The documents must be in either English or a Scandinavian language. Translations must be authorised. Originals must be presented if you are invited for an interview. OsloMet performs document checks in order to give you as a candidate a proper evaluation and ensure fair competition.

If you have documents that cannot be uploaded electronically, please contact hrtkd@oslomet.no

Before submitting the application documents to the Expert Committee, all applications will be reviewed by the faculty and applicants who do not meet the formal qualification requirements will not be submitted for assessment.

OsloMet has adhered to the principles in the DORA declaration and obliged the institution to follow the recommendations in this declaration.

We offer

• An exciting job opportunity at Norway’s third largest and most urban university
• Participation in a research group and a creative and inspiring academic environment
• Opportunities for academic development in a professional research environment
• Loan and pension arrangements through the Norwegian Public Service Pension Fund
• Beneficial welfare schemes and a wide range of sports and cultural offers
• Free Norwegian language classes to employees and their partners/spouses
• Workplace in downtown Oslo with multiple cultural offers

Practical information about relocation to Oslo and living in Norway

The position is remunerated in accordance with the Basic Collective Agreement for the Civil Service and OsloMets salary policy, job code 1352 Postdoctoral Research Fellow. The salary is NOK 543 500-702 100 per year, salary scale 60 -74. A higher salary may be considered for particularly well qualified applicants. 

 
Other information

If you would like more information about the position, feel free to contact

• Prof. Anis Yazidi, anis.yazidi@oslomet.no
• Prof. Pedro Lind, pedro.lind@oslomet.no

Deadline for application: January 19th 2022

Ref.:                            21/12515