Multi-Modal AI for Alzheimer’s Disease Detection
Alzheimer’s disease diagnosis combines information from multiple clinical and imaging sources. In this project, you will develop and evaluate machine learning methods that integrate these sources to improve diagnostic accuracy. You will work with real patient data and run experiments on a high-performance computing cluster.
What you’ll do
- Process and analyse multi-modal medical data
- Train and evaluate deep learning models for classification
- Investigate model interpretability and explainability
- Write a research paper and maintain a reproducible codebase
What you’ll learn
- Medical image analysis and multi-modal machine learning
- HPC / SLURM-based experiment management
- Scientific writing and reproducible research workflows
Ideal Candidate
- Python skills and working knowledge of machine learning
- Experience with PyTorch or TensorFlow
- Background in medical imaging or neuroscience
- Ability to attend bi-weekly meetings
Apply Send one PDF to mahfuzur.rahman.chowdhury@fau.de with the subject:
[Project (10 ECTS) – Alzheimer’s Detection ] <Your Full Name>
Email body (max. 200 words): Short motivation and your earliest start date. Attach as one PDF:
- CV
- Transcript of records
- Optional: links to code projects (GitHub, portfolio, etc.)
Incomplete applications will not be considered.