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Amsterdam UMC

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Postdoctoral Position in Multilayer Networks for Computational Neuroscience Amsterdam UMC in Netherlands

Degree Level

Postdoc

Field of study

Oncology

Funding

Available

Country flag

Country

Netherlands

University

Amsterdam UMC

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Keywords

Oncology
Computer Science
Mathematics
Artificial Intelligence
Connectomics
Python Programming
Alzheimer's Disease
Graph Theory
Neuropsychology
Social Neuroscience
Glioblastoma
Bioinformatic

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About this position

Amsterdam UMC’s MULTINET lab is offering a postdoctoral position focused on multilayer networks in computational neuroscience. The project investigates how early cellular and molecular changes in neurodegenerative and oncological diseases can lead to disruptions in brain networks and subsequent cognitive decline.

The researcher will use multilayer network theory to model, quantify and understand interactions across different biological scales. The work will build on the multiSCALE Python toolbox and apply computational approaches to diseases including Alzheimer’s disease and glioma.

The position is embedded in a collaborative research environment involving the MULTINET lab and the Adore – Research Community Biocomputation group. The broader research setting includes Amsterdam UMC, Cancer Center Amsterdam and Amsterdam Neuroscience, bringing together expertise in computational methods, network analysis, bioinformatics and disease biology.

The postdoctoral researcher will contribute to a multidisciplinary team working at the intersection of artificial intelligence, mathematics, bioinformatics, graph theory, network neuroscience and connectomics.

Funding details

Available

What's required

Applicants must hold a PhD in artificial intelligence, mathematics, bioinformatics, or a closely related discipline; have experience developing and implementing computational methods; possess strong programming skills, preferably in Python; communicate complex ideas clearly to non-specialists; and have excellent written and verbal English communication skills, self-motivation, and the ability to work effectively in a multidisciplinary environment.

How to apply

Submit the application only through the website linked in the first comment. Do not apply by email or LinkedIn.

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