Job summary
You will work on the Identifying Digital Endpoints to Assess Fatigue, Sleep and Activities of Daily Living in Neurodegenerative Disorders and Immune-mediated Inflammatory Diseases (IDEA-FAST) project. The IDEA-FAST project is a 5-year IMI2 project run by a consortium of 46 partners across 15 countries in Europe. The project aims to identify digital endpoints that provide reliable, objective, and sensitive evaluation of activities of daily life (ADL), disability and health related quality of life (HRQoL) for neurodegenerative diseases.
You will contribute to the development of the state-of-the-art data management platform and analytical environment to address the needs of data standardisation, integration, sharing, analysis, and archive for the project. This will ensure clinical data (e.g., demographics, diagnosis, laboratory tests, clinical events, medications, patient-reported outcomes) and data collected from various digital devices (e.g., physical/bio-physiological data, EEG data, mobile data) generated from the project meet quality and compliance requirements and enable project participants to perform integrated data modelling and analysis to identify digital endpoints for fatigue and sleep disturbances. You will also be expected to contribute to the development of novel algorithms for identifying digital endpoints, and the implementation of these algorithms into the platform’s analytical environment.
Duties and responsibilities
Key Responsibilities
- To curate and integrate data collected during the project with existing datasets on the developed platform.
- To develop data analytical pipelines for clinical and sensor data collected in IDEA-FAST.
- To develop and integrate data analytical pipelines into the IDEA-FAST data analytics environment.
- To attend regular internal and external project meetings and report working progress.
- To promote research internally and externally at national and international conferences by presentation, publication, and demonstration.
- To promote the reputation of the Groups, the Departments, and the College.
- Any other duties commensurate with the grade of the post as directed by the line manager / supervisor.
- To undertake any necessary training and/or development
- To undertake appropriate administration tasks
- Where Imperial or funder conditions necessitate, you will be required to complete timesheets for your work on projects in a timely manner.
Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.
Essential requirements
- Research Associate: Hold a PhD in computer science, software engineering,
bioinformatics or a closely related discipline.
- Software development experience with Java or Python
- Experience in building & deploying machine learning models
- Experience with database engines (MongoDB, PostgreSQL/MySQL)
- Experience in handling/processing large & complex datasets
- Practical experience within a research environment and/or publication in relevant & refereed journals
- Good knowledge in statistics and machine learning
- Good understanding of data management procedure and tools
- Good knowledge of modern programming paradigm and IT concepts (cloud
computing, parallel computing) management technology (e.g. Docker, Openstack)
- Strong coding skills & problem-solving skills
- Excellent communication skills to collaborate with researchers and staff at the DSI
and other IDEA-FAST project partners to best, understood requirements, and
summarise data processing/analysis via written/oral communication
- Ability to work in a fast-paced, collaborative, and iterative development environment
- Commitment to software quality and a strong attention to detail
- Experience of planning & progressing work to agreed timescales within general
guidelines. Able to manage multiple activities simultaneouslyAbility to present themselves at conferences and seminars with authority and
- coherence.
- Discipline & regard for confidentiality and security at all times
Further information
To apply, please click on the ‘Apply’ button above.
For queries regarding the application process contact Arek Ciechacki at a.ciechacki@imperial.ac.uk