# Research Scientist, Computational Neuroscience · Good AI Labs

> Develop computational approaches to learning, memory and adaptation that can improve embodied intelligence.

URL: https://www.goodailabs.com/careers/research-scientist-computational-neuroscience/
Date: 2026-10-13
Last updated: 2026-10-13
Work arrangement: Remote-first


Related work: [Research at Good AI Labs](https://www.goodailabs.com/research/)

## Applying

Email your application to research@goodailabs.com, with the role title in the subject line. Include your location and availability. Please share only material you have permission to disclose.

Email: research@goodailabs.com. Include the role title in the subject line.


Good AI Labs is hiring a Research Scientist in Computational Neuroscience to investigate mechanisms that help artificial systems learn, retain useful experience and adapt. We are interested in scientific ideas that can lead to more capable foundational models and robots that continue learning as they interact with the world.

You will develop computational hypotheses, implement and train models, and test their behaviour in controlled environments. Simulation and reinforcement learning provide practical settings for studying skill acquisition, memory and adaptation. The role calls for depth in the science and the ability to turn that understanding into a working learning system.

## Responsibilities

- Develop computational accounts of learning, memory, credit assignment or adaptation with a clear experimental formulation.
- Implement and train models that test how a proposed mechanism affects acquisition, retention, interference and transfer.
- Design simulated tasks and behavioural experiments that distinguish competing explanations.
- Work with machine-learning researchers to incorporate useful mechanisms into continual-learning and reinforcement-learning systems.
- Compare methods under controlled experience and compute budgets, examining behaviour across repeated learning rather than a single task.
- Connect the findings to the neuroscience literature and identify which conclusions can inform further robotics research.

## Qualifications

- BS, MS or PhD in computational neuroscience, cognitive science, machine learning, applied mathematics or a related field, or demonstrated research of equivalent depth.
- Original computational research on learning, memory or adaptive behaviour, with experience implementing and training models.
- A research record demonstrated by leading contributions in neuroscience, cognitive science or machine learning, or computational systems and technical work of comparable scientific depth.
- Strong mathematical modelling and statistical inference, including the ability to compare models and identify what an experiment can establish.
- Proficiency in Python and experience with numerical methods or deep-learning frameworks for model training and analysis.
- The ability to work across scientific disciplines and defend a proposed learning mechanism with both theoretical reasoning and experimental results.

## Preferred experience {#experience-that-would-help}

- Continual learning, memory consolidation, credit assignment, sensorimotor learning or adaptive behaviour.
- Reinforcement learning, recurrent models or simulated environments for studying learning over time.
- Connecting computational theory to behavioural evidence or transferring a scientific hypothesis into an implemented learning method.

## Application materials {#what-to-include-in-your-application}

Include your CV and two or three research contributions. Explain your role in one computational model, how it was trained or fitted, and which evidence supports its account of learning. We are interested in the depth of the work whether it came from a degree programme, an industrial lab or independent research.

Contact: research@goodailabs.com