In September 2022, our team undertook a global search for longitudinal datasets across the world to offer a springboard for developing new and innovative mental health research while harnessing existing data resources. In August 2023, we submitted our report on the Landscaping project to Wellcome. In this report, we provided 1) a list of all longitudinal datasets we identified worldwide; 2) a comprehensive review of the richness of those datasets for mental health research; and 3) an in-depth analysis of a selection of the largest ongoing datasets to uncover innovative resources for researchers that can support transformative mental health research.
In furthering this goal, the Wellcome Trust has funded the creation and development of a platform for longitudinal mental health data to convert and expand the information included in our report into an online searchable tool that will be freely accessible.
We are seeking two Research Assistants to be part of an in-house team at King’s College London that work alongside a range of partners including a web developer and AI consultant, transparency and engagement coordinator and Lived Experience Experts (LEEs). As part of this role, the post holder will support the development of a new online platform that will hold meta-data for more than 3,000 longitudinal datasets from across the world. The post holder will be responsible for conducting reviews of information about longitudinal datasets and extracting relevant details for the new online platform, ensuring that the information is accurate and up to date, liaising with internal and external collaborators, participating in the analysis of the metadata, searching for additional repositories of longitudinal datasets, thinking creatively about expansion and improvement of the platform, disseminating updates about the platform on social media and other channels and updating the pool of longitudinal datasets with new information.
Both roles will be offered on full-time, fixed term contracts for 12 months.
- Conduct reviews of information about longitudinal datasets and extracting relevant details for a new online platform
- Keep a pool of 3000+ datasets and 200+ repositories organised, accurate and up to date using manual or artificially intelligent means
- Search predetermined repositories and online for additional repositories of longitudinal datasets to expand our existing pool of 3000+ longitudinal datasets for further reviewing.
- Check, troubleshoot and support the finetuning of a new data entry system.
- Assist in training an open-source thematic similarity AI model for classifying dataset descriptions.
- Work alongside Lived Experience Experts (LEEs) identifying datasets and repositories ‘off the beaten track’ (e.g., review of grey literature)
- Liaise with internal and external collaborators
- Participate in the analysis of metadata of 3000+ longitudinal datasets
- Think creatively about the expansion and improvement of a new online platform
- Disseminate updates about an online platform on social media
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.
Skills, knowledge, and experience
1. Educated to degree level in psychology, computing, technology or related disciplines
2. Professional or academic experience developing websites, platforms or applications
3. Knowledge or experience in psychology, mental health and related disciplines
4. Experience managing a varied workload with conflicting priorities
5. Ability to work independently and in a team
6. Computer knowledge including Microsoft Word, Excel, Access, PowerPoint, Outlook and Canva
7. Effective and courteous written and verbal communication skills
8. Organised with good time management skills
9. Organisation skills in filing, document management and general administrative skills
1. Knowledge of longitudinal datasets
2. Training or certifications in computer programming and artificial intelligence
3. Experience in managing very large volumes of data
4. Experience using statistical computing such as R or STATA
The selection process will include a criteria based shortlisting process and in-person interview including assessment task. Interviews will be held the 2nd week of December 2023. In-person interviews are preferred but online interviews may be accommodated if necessary.