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Summer School in Computational Biology

A 2-week hands-on summer school where students (M. Sc.-level and up) learn to computationally model biological systems, analyze omics data, and apply AI to biomedical challenges

Summary

The Summer School in Computational Biology was founded in 2015 by the Computational Biology Network at the University of Coimbra as a means to facilitate access to the Computational Biology field by students and researchers with either biological or exact sciences backgrounds. In the first two weeks of September each year we receive 20 – 30 international students who wish to acquire skills in Computational Biology. The course is intensive and targeted to students from the M. Sc. to post-doctoral levels with limited or no previous exposure to the field, although applications from B. Sc. students with outstanding CVs/skills are also considered. It offers a broad perspective on the field and has four main components:
*Introductory lectures on mathematics and physics for biologists, and biology for exact sciences students (parallel tracks)
* Lectures on specialized Computational Biology topics
* Seminars by leading scientists on recent developments
* Small research projects where the students have the opportunity to apply the acquired skills to real research problems
Illustrative applications emphasize biomedical problems.

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Program Features

    • Strong hands-on component
    • Intensive programme
    • Expert lecturers and tutors
    • Meet students from all over the world.

Program Details

DatesSeptember 2-13, 2025
Ages20+
FeesRegistration fee: €120
LocationCoimbra, Portugal

Camp details

Topics covered:
* Core knowledge for modeling biological systems
* Molecular dynamics for lipid membranes and proteins
* Protein-ligand interactions and drug discovery
* Data Science and Artificial Intelligence in Biology and Biomedicine
* Genomics/Transcriptomics to characterize cellular mechanisms
* Kinetic modeling of metabolic and signaling processes
* Modeling of physiological systems
* Computational Neuroscience / NeuroAI

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