We are seeking two Research Associates to support research in structured and unstructured text/electronic health record analysis and/or Internet of Things (IoT) and time-series data analysis for clinical applications.

You will play a central role in developing the neuroscientific and machine learning work and become a member of the research group at the UK Dementia Research Institute Care Research & Technology Centre (UK DRI CR&T), working with Prof. Payam Barnaghi and Prof. David Sharp (https://ukdri.ac.uk/centres/care-research-technology).

The research will involve working with partially labelled data, natural language processing, unstructured and semi-structured data analysis, and applying semi-supervised learning approaches to develop decision support and predictive models. The technical work will also require integration, verification and validation of the designed solutions using UK DRI’s ongoing clinical study data. You will work with the software development and clinical teams within the centre.

We are looking for creative and enthusiastic researchers who can take on a challenging role with considerable scope for independent scientific achievement and personal growth. You will be supported in your career development, including in the application for independent research funding both from the UK DRI and externally.

The post will suit highly motivated researchers interested in addressing real-world challenges and creating end-to-end solutions.

Below are examples of the group’s recent work in this area.

• https://arxiv.org/pdf/2101.07007.pdf
• https://arxiv.org/pdf/2011.13916.pdf
• https://arxiv.org/pdf/2011.00851.pdf
• https://arxiv.org/pdf/2010.09633.pdf
• https://arxiv.org/pdf/1910.04112.pdf

Duties and responsibilities

You will focus on analysing continuous in-home observation and measurement data, clinical observations and electronic healthcare records at population and individual levels.

Your main responsibilities will include:

• To take initiatives in the planning of research
• To conduct data analysis
• To maintain accurate and complete records of all findings
• To write reports for submission to research sponsors
• To present findings to colleagues and at conferences
• To submit publications to refereed journals
• To provide guidance to staff and students

Essential requirements

• Research Associate: Hold a PhD (or equivalent) in Engineering, Computer Science, Computational Neuroscience, Mathematics, Physics, or related discipline
• Research Assistant: Near completion of a PhD (or equivalent) in Engineering, Computer Science, Computational Neuroscience, Mathematics, Physics, or related discipline
• Knowledge of machine learning and computational modelling
• Knowledge of research methods and statistical procedures
• Practical experience within a research environment and publication in relevant and refereed journals
• Dealing with specific groups of people, e.g., sponsors, patients, clinical groups
• Experience in machine learning frameworks and Python or MATLAB programming

For more information, please refer to: https://www.imperial.ac.uk/jobs/description/MED02329/research-associate-x2