Neuromatch Academy: Buscando estudiantes y educadores interesados en neurocomputación

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POR Giovanna Guerr… -

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Wondering which Neuromatch Academy course is right for you? Applications close 15 March, so we're walking you through your options to help you decide.


All courses are live and mentored online, with small pods, a dedicated TA, and a collaborative project.


You can apply for up to three roles and rank your preferences, whether as a student, a Teaching Assistant, or a combination of both. You can only accept one role. There is no cost to apply.


Read on and find the right fit for you this July!

Your starting point in computational neuroscience.

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Computational Neuroscience: 6-24 July, 2026

This course integrates cutting-edge advances in machine learning and causality research with state-of-the-art modeling approaches in neuroscience.

Project topics:

  • Neurons 
  • fMRI
  • ECoG
  • Behavior & Theory 

Prerequisites:

  • Python: Students should be familiar with variables, lists, dicts, the numpy and scipy libraries as well as plotting in matplotlib.
  • Math: Students should know linear algebra, probability, basic statistics, and calculus (derivatives and ODEs). 
  • Neuroscience: Students should be familiar with foundational neuroscience concepts.
Have some foundations? Build on them with hands-on deep learning.

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Deep Learning: 6-24 July, 2026


Dive into deep learning with a code-first, TA-guided curriculum that teaches ethically responsible methods to tackle real scientific problems.

Project Dataset Options:

  • Computer Vision
  • Natural Language Processing
  • Reinforcement Learning
  • Neuroscience 

Prerequisites:

  • Python: We expect students to be familiar with variables, lists, dicts, the numpy and scipy libraries as well as plotting in matplotlib.
  • Math: Students should know linear algebra, probability, basic statistics, and calculus (derivatives and ODEs). 
For those with Comp Neuro and Deep Learning experience, come explore NeuroAI.

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NeuroAI: 13-24 July, 2026


Explore the core challenge of intelligence: generalization. This course covers task structure, neural micro- and macro-circuits, learning rules, and approaches for understanding complex data streams.

Project topics:

  • Computer Vision
  • Natural Language Processing
  • Reinforcement Learning
  • Neuroscience 

Prerequisites:

  • Have taken Comp Neuro and Deep Learning courses or equivalent 
  • Python: Intermediate proficiency. We expect students to be familiar with variables, lists, dicts, the numpy and scipy libraries, PyTorch, and plotting in matplotlib. 
  • Math: Students should know linear algebra, probability, basic statistics, and multivariable calculus. 
Teach students worldwide, build your resume, and get paid for it.

Join Neuromatch Academy as a virtual Teaching Assistant this July. We are hiring Teaching Assistants for Computational Neuroscience, Deep Learning, and NeuroAI. Support small-group learning pods and mentor students in a collaborative, global environment.

As a Teaching Assistant, you will: 

  • Receive compensation for your time and training
  • Learn the peer-to-peer education model used in Neuromatch courses
  • Build connections with peers, researchers, and educators worldwide
  • Gain hands-on experience in mentorship, scientific communication, and teaching to build your resume

You can apply for up to three roles and rank your preferences, whether as a student, a Teaching Assistant, or a combination of both.

All TAs should have a strong background in Python and the specific course topic. We strongly encourage past students to apply!