Research Assistant - Academic Neuroscience

KINGS COLLEGE LONDON; London; On-site; GBP 38,000 - 39,000

Job description

Organisation/Company KINGS COLLEGE LONDON

Research Field Architecture Engineering Physics

Researcher Profile Recognised Researcher (R2) First Stage Researcher (R1)

Country United Kingdom

Application Deadline 1 Apr 2025 - 00:00 (UTC)

Type of Contract Other

Job Status Full-time

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure? No

Offer Description

About us

King’s College London is one of the world’s leading universities, renowned for its excellence in research, education, and clinical innovation. The Sleep and Brain Plasticity Centre, based within the Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience (IoPPN), is at the forefront of cutting-edge sleep research, integrating neuroscience, computational modelling, and clinical applications to advance our understanding of sleep-related brain processes.

A key focus of our centre is the development and refinement of sleep EEG research pipelines, enabling high-resolution analyses of sleep architecture, neural oscillations, and cognitive function.

About the role

King’s College London invites applications for a highly skilled specialist to join our research team at the Sleep and Brain Plasticity Centre. The successful candidate will play a critical role in executing and finalising the bespoke SleepCity EEG project pipeline, contributing significantly to ongoing research in sleep neurophysiology.

You will contribute to the SleepCity EEG project, ensuring the successful execution and optimisation of our bespoke EEG research pipeline. The appointed candidate will play a central role in advancing our research initiatives, enhancing our capabilities in data processing, analysis, and interpretation of sleep EEG.

This position requires expertise in sleep EEG processing and analysis, with a strong background in non-linear EEG methods, spectral analysis, and network-based approaches to sleep dynamics. The ideal candidate will have extensive experience in Python programming and be proficient in handling large EEG datasets using publicly available polysomnography (PSG) analysis software.

The role involves developing and optimising the EEG analysis pipeline, overseeing the successful analysis and management of large-scale sleep EEG datasets, and ensuring seamless coordination with key collaborators. The candidate will be expected to train and support team members in using EEG analysis protocols, deliver weekly progress updates to the line manager, and contribute to manuscript preparation.

Given the complexity of our current bespoke EEG pipeline, the candidate’s demonstrated experience in computational physics and dynamical systems modelling will be invaluable. Their strong programming background, including Python, C++, and Java, as well as their ability to work efficiently with shell scripting and remote server-based computational workflows, would be ideal.

This is a unique opportunity to contribute to pioneering research in sleep neurophysiology and EEG signal analysis within a leading academic institution. The position is ideal for a researcher with a strong computational background who is eager to apply their expertise in EEG processing, sleep science, and network-based analysis methods to a highly specialised research setting.

This post will be offered on a full-time, fixed term contract for 12 months.

About you

• Expertise in sleep EEG analysis, including spectral analysis, non-linear EEG methods, and network-based approaches to sleep dynamics.
• Proficiency in Python programming, with experience in EEG signal processing and computational modelling of sleep architecture.
• Demonstrated experience working with large-scale EEG datasets.
• Familiarity with polysomnography (PSG) data analysis.
• Background in computational physics, neuroscience, or biomedical engineering.
• Ability to work with remote server-based computational workflows.
• Proven ability to manage research projects independently.
• Strong collaborative skills, with experience coordinating with interdisciplinary teams.
• Track record of contributing to scientific publications.
• Experience with advanced EEG connectivity analyses.
• Knowledge of programming languages beyond Python, such as C++, Java, or MATLAB.
• Familiarity with machine learning approaches for EEG data analysis.

Grade and Salary: £38,482 per annum, including London Weighting Allowance

Job ID: 110965

Close Date: 01-Apr-2025

Contact Person: Peter Goadsby / Ivana Rosenzweig

Contact Details: [e-mail] / [e-mail]