Computational Neurobiology and Alzheimer’s Disease

The Salta group studies the cellular and molecular mechanisms underlying brain resilience and neurodegeneration, with a particular focus on adult hippocampal neurogenesis and Alzheimer’s disease. Our research combines different omics, iPSC cultures, imaging, and integrative computational approaches to understand how the brain responds to aging and disease, and whether these mechanisms can be harnessed to improve cognitive function.

Project Description

The student will join a PhD project investigating the effects of lifestyle interventions, particularly physical exercise, on Alzheimer’s disease-related neuroinflammation using human iPSC-derived microglia models.

The student’s project will primarily focus on computational biology and data analysis, centered on the integration and interpretation of multi-omics datasets generated from iPSC-derived microglia-like cells. The project aims to understand how exercise-associated molecular signatures may influence neuroinflammatory and neurodegenerative trajectories relevant to Alzheimer’s disease.

The student will work closely with the research team and participate in discussions on experimental design, data interpretation, and scientific literature.

Activities

The student will:

• Analyze transcriptomic and proteomic datasets
• Perform computational and statistical analyses
• Contribute to the interpretation of biological findings
• Read and discuss relevant scientific literature
• Attend and participate in lab meetings and journal clubs
• Present project progress and findings

The student will develop and pursue an independent research question within the project, taking ownership of a specific aspect of the study from data analysis to interpretation and presentation of results.

Requirements

We are looking for a highly motivated student with an interest in neuroscience, neurodegeneration, computational biology, or bioinformatics.

Experience with one or more of the following is appreciated but not strictly required:

• R or Python programming
• Transcriptomics (bulk RNA-seq) or proteomics analysis
• Statistics and data visualization
• Image analysis or machine learning methods
• Neuroscience or cell biology background

The student should be available full-time for at least 5 months. Longer periods are appreciated. We understand that some students may need to combine the internship with other work to support themselves, and we will take this into account when planning the project and timeline.

Conditions

This internship is unpaid and does not include financial support from the institute.