Priority areas
Applications should result in training opportunities in data science to upskill health and bioscience researchers, relevant to one or more of the following themes:
- data stewardship, management and sharing
- manipulation and analysis of complex large-scale data
- data modelling skills and training in data exploration, interpretation, calibration or validation
- integration of different types of data, such as imaging and genomics
- improving software, computing, infrastructure, architecture and data engineering knowledge contextualised for data-intensive biosciences
- statistics or mathematics skills contextualised for data-intensive biosciences.
Data science training in health and bioscience may be relevant to a number of inter-related areas such as bioinformatics, computational biology, healthcare informatics and systems biology, neuroscience, the social sciences including health economics, computational social science and psychology, in addition to researchers working at the interface of the social and biosciences, for example biosocial.
Pertinent data and technical challenge areas include (but are not limited to) genomics and gene expression, proteomics and metabolomics, image analysis and phenotyping, digital health data (including new and emerging forms of data), AI and machine learning, data visualisation, modelling, and reproducibility/good research practice (for example experimental design, workflows, fostering FAIR data principles) within data-intensive science, the secondary analysis of administrative, cohort and panel studies.
A key objective of this programme is to give researchers the self-confidence and skills to manage and analyse their own data.
Training approaches
Training may be delivered through a range of activities, mechanisms and approaches, within one or more of the following priorities:
- new, improved and expanded content, for example new learning materials, trainer resources
- new ways of working, for example development of high-quality, open peer-learning environments, innovative pedagogy
- approaches to broaden availability, suitability and usability of training resources for continuing professional development across different career stages, skill levels, and sectors within health and biosciences
- integration and alignment of training resources to increase coherence and promote skills development pathways
- intensive face-to-face short-courses and ‘summer schools’ to meet priority skills needs (foundational or accelerator skills within scope)
- virtual and remote training, including combinations of self-directed and trainer-supported activity
- train-the-trainers approaches to strengthen capability across the UK to deliver training.
Who should training be directed at?
Training should be broadly available to the UK research and innovation community, with a strategy to engage both academic, industry and clinical researchers where relevant.
This call will contribute to building digital workforce capacity and skills for data-intensive science in the UK, which are in high demand within the health and biosciences.
Consideration must be given to research culture and ensuring equality and inclusion in delivering the training offering (for example outreach to underrepresented groups, flexible access, approaches to selecting course participants). Offers must be outward facing beyond individual research organisations and geographic locations, and must support continuing professional development across career stages. The call is not intended to directly support MSc or PhD programmes.
Applications should clearly outline the training need and how they uniquely fit into the wider training landscape, including opportunities for synergy with existing training resources and activities where relevant.
Funding
A total budget of £5 million is available through the UKRI Innovation Scholars programme to support five to 10 awards for up to 24 months. Awards should ideally start by 14 February 2021.
We will support projects of a range of scale, but expect programmes to be ambitious and deliver at regional or national scale. Direct costs associated with training will be funded at 100% full economic cost (fEC). Staff and Estates/Indirect costs will be funded at 80% fEC. Standard UKRI Grant Terms and Conditions apply.
Please note the following exclusions:
- full or partial PhD studentships
- full or partial MSc/MRes studentships (UKRI does not provide funding for stand-alone masters training grants)
- apprenticeships
- conference attendance/travel bursaries
- subscriptions to existing platforms
- training aimed primarily at non-UK based researchers and innovators
- training aimed primarily at individuals undertaking undergraduate or postgraduate study
- large infrastructure costs. Equipment required to carry out the project will be considered.
