Research Assistant @ University of Nottingham
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Job Details
Overview
Join the Computational Neuroimaging research team at the University of Nottingham's Sir Peter Mansfield Imaging Centre (SPMIC) within the School of Medicine. In this role, you will assist in developing neuroimage analysis methodology for brain Magnetic Resonance Imaging (MRI) using in-silico biophysical modelling.
Role Responsibilities
- Conduct computer simulations and software generation.
- Perform literature searches and data analyses.
- Draft reports and contribute to academic research.
- Support neuroimaging research and mapping of brain connectivity.
Team and Environment
You will work under the leadership of Prof. Stam Sotiropoulos, in a well-established team known for pioneering neuroimaging techniques including diffusion MRI and research funded by the European Research Council (ERC). The position offers hybrid working options and a wide range of staff benefits.
Qualifications
An undergraduate degree in a relevant computational domain such as engineering, physics, neuroscience, computer science, or applied mathematics is required. Proficiency in computer programming (Python, C++, Matlab) and scientific computing is essential. A Master’s degree and prior research experience in neuroimaging data analysis are desirable.
Employment Details
This is a fixed-term position available full-time (36.25 hours per week) or part-time (minimum 29 hours per week), starting from 5th January 2026 for a duration of six months (full-time) or seven months (part-time).
Key Skills/Competency
- Neuroimaging
- MRI
- Computational Analysis
- Biophysical Modelling
- Python
- C++
- Matlab
- Data Analysis
- Simulation
- Report Drafting
How to Get Hired at University of Nottingham
🎯 Tips for Getting Hired
- Customize your resume: Tailor skills to neuroimaging and programming.
- Highlight research expertise: Emphasize simulation and data analysis.
- Align with University values: Showcase training and academic achievements.
- Prepare for interviews: Review technical neuroimaging concepts and methodologies.