at Umeå center for Functional Brain Imaging (UFBI) and related institutes/labs.
Two Postdoctoral scholarship positions in Machine Learning with focus on Brain analysis at Luleå University of Technology.
The department of Computer Science, Electrical and Space Engineering at Luleå University of Technology (LTU) is offering two scholarships for a Postdoctoral Fellow to carry out research with the Machine learning group in the area of Brain data analysis for inner speech decoding. Machine learning focuses on computational methods by which computer systems use data to improve their own performance, understanding, and to make accurate predictions and has a close connection to applications.
Project description The postdoctoral positions are part of a funded 2-year project supported by Kempestiftelsen, focused on decoding inner speech using multimodal EEG and fMRI data. The successful candidates will work with two unique bimodal datasets, enabling investigation into both the temporal and spatial aspects of inner speech. Using cutting-edge machine learning techniques, including deep neural networks and graph-based models, the project will explore how to optimally fuse EEG and fMRI data and develop accurate inner speech decoding frameworks. This interdisciplinary project combines cognitive neuroscience and AI. It is hosted at Luleå University of Technology (LTU) within the Brain Analysis of the Machine Learning Group and benefits from strong institutional support, access to MRI-compatible EEG hardware, and high-performance GPU infrastructure.
Postdoctoral Fellowship (2 years) in research project on biomarkers for cognitive aging at the Department of Psychology
This project will study blood markers for cognitive aging, i.e., measurements in blood that can predict individuals' cognitive development in aging and theirs risk of dementia. Such markers will be important for better personalizing prevention and treatment of age-related cognitive decline in the future. The project involves statistical analyses of longitudinal changes in levels of many different blood proteins, and how these changes are related to cognitive changes and established markers for Alzheimer's disease. The project may also include machine learning methods to estimate individuals' biological age.
The project is based on existing data from a prominent longitudinal aging study, the Betula Project, as well as the UK Biobank. The candidate will handle, process, and statistically analyze large amounts of data on blood markers, cognitive tests, and health and lifestyle factors. The project will be conducted on-site in Umeå, and remote work is not possible.
Qualifications To be eligible for a postdoctoral fellowship, the person must have obtained a doctoral degree or a foreign degree deemed equivalent to a doctoral degree. This eligibility requirement must be met no later than the time the decision on the fellowship recipient is made. To be considered for a postdoctoral fellowship, the candidate should primarily have obtained their degree no more than three years before the application deadline. If there are special reasons, candidates who obtained their doctoral degree earlier may be considered. Special reasons include leave due to illness, parental leave, clinical service, assignments within trade union organizations, or other similar circumstances.
