The Department of Brain Sciences at Imperial College London is looking to fill a Research Associate position to contribute to our research in autonomic neurosciences and syncope, specifically applying machine learning to a large and diverse, curated clinical dataset.
The candidate should have a PhD or MSc in a relevant field such as Neuroscience, Cardiovascular Science, Computer Science, Mathematics, or related disciplines with a focus on machine learning, deep learning or data science for clinical applications.
The postholder will become a member of the research group in the Department of Brain Sciences working with Dr Melanie Dani, Professor Payam Barnaghi and Dr Gregory Scott. They will be expected to carry out research independently, submit publications to refereed journals and attract external research funding.
This work will focus on interrogating and applying machine learning to one of the largest and most diverse clinical syncope datasets (tilt table tests) to our knowledge, and thus answering key questions about the physiology and mechanisms of syncope and dysautonomia, and contribute to better classifying and naming this diverse set of disorders.
We are looking for a creative and enthusiastic researcher who can take on a challenging role with considerable scope for independent scientific achievement and personal growth. The successful candidate will play a central role in developing the scientific and machine learning work within the Department of Brain Sciences.
The post will suit a highly motivated candidate who is interested in addressing real-world challenges and creating end-to-end solutions.
The research will involve working with partially labelled data, performing unstructured and semi-structured data analysis, and applying supervised and unsupervised learning approaches to develop decision support and predictive models. The technical work will also require integration, verification and validation of the designed solutions using existing clinical study data. Experience in software development and programming and practical applications of machine learning in clinical data analysis will be highly desirable. The candidate will be supported in their career development
- PhD in cardiovascular science, neuroscience, computer science or a closely related discipline, or equivalent research, industrial or commercial
- Knowledge of clinical studies, cardiovascular science or neuroscience
- Knowledge of research methods and statistical procedures
- Practical experience within a research environment
- A record of high-quality publications in international peer-reviewed journals
- Ability to organise your own work with minimal supervision
- A creative approach to problem-solving; a “doer”.
- A unique opportunity to work on an exciting project that can transform our understanding and management of major clinical problems
- Join a highly multi-disciplinary lab and a world-leading institution
- Progress your academic career with support from the lab and department, in an institution with dedicated support for research associates.
This is a Fixed term (5 years) part time role based at our London Campuses.
Please contact Dr Melanie Dani (melanie.dani@nhs.net or m.dani@imperial.ac.uk) for further information.
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