Postdoc: Habit Neuroscience & Adaptive Learning (fMRI)

Postdoc: Habit Neuroscience & Adaptive Learning (fMRI)

Full-Time 30000 - 40000 Β£ / year (est.) No working from home possible
Job Search Place Limited

At a Glance

  • Tasks: Explore the brain's habits and learning through cutting-edge fMRI research.
  • Company: Join the prestigious University of Oxford in a supportive research environment.
  • Benefits: Gain valuable experience, mentorship, and opportunities for professional development.
  • Other info: Collaborative atmosphere with excellent career advancement potential.
  • Why this job: Make a real impact in understanding how we learn and adapt to uncertainty.
  • Qualifications: DPhil/PhD in Cognitive Neuroscience with skills in experimental design and data analysis.

The predicted salary is between 30000 - 40000 Β£ per year.

Job Search Place Limited is seeking a Postdoctoral Researcher in Cognitive Neuroscience at the University of Oxford. This role focuses on investigating the neural mechanisms behind habitual behaviour and how learning adapts to uncertainty.

Applicants should possess a DPhil/PhD in a relevant field and demonstrate strong skills in experimental design and data analysis.

The position promises a supportive work environment with numerous opportunities for professional growth.

Postdoc: Habit Neuroscience & Adaptive Learning (fMRI) employer: Job Search Place Limited

Job Search Place Limited offers an exceptional work environment at the prestigious University of Oxford, where you will engage in cutting-edge research on habit neuroscience and adaptive learning. With a strong emphasis on professional development, our supportive culture encourages collaboration and innovation, making it an ideal place for researchers eager to make meaningful contributions in their field.

Job Search Place Limited

Contact Details:

Job Search Place Limited Recruitment Team

We think you need these skills to ace Postdoc: Habit Neuroscience & Adaptive Learning (fMRI)

Cognitive Neuroscience
Experimental Design
Data Analysis
Neural Mechanisms
Habitual Behaviour
Adaptive Learning
Uncertainty Handling