UK DRI Postdoctoral Research Associate
Employer
UK DRI at King's College London
Location
London, England, U.K.
Principal Investigator
Professor Chris Shaw
Contact
Dr James Bashford, james.bashford@kcl.ac.uk
Description
Researchers at the UK Dementia Research Institute at King's College London are using innovative approaches to explore the biological mechanisms involved in neurodegenerative diseases. Their goal is to defeat dementia by uncovering vital new knowledge that will lead to the design of smarter diagnostics and effective treatments. The team aims to understand the fundamental biological processes involved in dementia at a molecular level—and to use that knowledge to design new ways to diagnose and treat disease more precisely.
The researcher recruited to this post will help drive the setup of multimodal home monitoring of patients with the neurodegenerative disorder amyotrophic lateral sclerosis (ALS). This post will form a strong academic link between Professor Chris Shaw at UK DRI at King's College London and Professor David Sharp at UK DRI at Imperial College London. Close liaison with expert machine-learning teams at the University of Surrey will be integral. Ultimately, we aim to answer important questions about environmental influences on disease progression in ALS and the development of novel biomarkers to advance drug discovery. This position is funded by the UK DRI Cross Centre Postdoctoroal Programme.
Contract: Fixed-term for 36 months or until 31st Jan 2024
Hours: Full-time
This post will require a background in neuroscience and familiarity with clinical study design, although specific knowledge or experience of ALS is not essential at this stage. Ideally, the postdoctoral researcher would have gained experience in MATLAB coding and be eager to work alongside software engineers in the development of a remote data transfer strategy.
Specific aims of this project:
a. To integrate the remote assessment of muscle activity in ALS within the Dementia Research Institute home monitoring digital platform, including robust and secure data transfer and analysis protocols.
b. To investigate potential relationships between muscle activity and measures of patient behavior (e.g. patient movement), physiology (e.g. pulse/blood pressure variation), and sleep quality in the home.
c. To establish a home-based multimodal biomarker that tracks the neurodegenerative process in ALS.
Estimated timeline for the post:
0-9 months: Study documentation will be produced (protocol, patient information sheet, etc.) and ethical and study approvals obtained; liaison with patient focus group involving patients recruited to previous studies at King's; training in equipment use and analytical/monitoring methods; purchase required quantity of recording devices.
9-24 months: Recruitment of 20 ALS patients for continuous home measurement of gross mobility, vital signs, and sleep alongside weekly home muscle recordings; data collection.
24-36 months: Assimilate data; involve machine-intelligence team at University of Surrey; perform statistical analysis; prepare manuscripts for publication; present work at international conferences. evelopment of novel biomarkers to advance drug discovery.
The above list of responsibilities may not be exhaustive, and the post holder will be required to undertake such tasks and responsibilities as may reasonably be expected within the scope and grading of the post.
Requirements
Essential criteria
Ph.D. awarded in neuroscience or Ph.D. in neuroscience near completion.
Previous involvement in key aspects of clinical neuroscience research (e.g., clinical drug trials, patient recruitment, data collection).
To have presented at national or international conferences, including poster and oral presentations.
To have the necessary skills and dedication to setup, recruit for, and run a clinical study.
To be familiar with common biostatistical techniques.
Desirable criteria
1st Class or 2.1 awarded at undergraduate degree.
Awarded academic prizes or awards.
Knowledge of the national research ethics service approval process.
To have published high-quality work in peer-reviewed journals.
To have plans to pursue a long-term research career.
To have the mathematical background to pursue complex biostatistical methods (using the package "R") and bioengineering analysis (using the package "Matlab").
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