Summary

Work toward the establishment of a cross-University data science consultancy community, supported by a modestly larger surplus-generated Bayes Data Science Consultancy Unit (DSCU).

The DSCU team would work to increase academic engagement with external industry partners, by triaging opportunities and partners and executing short-term scoping projects beyond the bandwidth of academic researchers, in order to develop larger-scale strategic R&D engagements and provide early-stage proof-of-concept demonstrators that will lead to subsequent engagement with academics and students.

Project Description

We propose to set up a Bayes Data Science Consultancy Unit (DSCU) to link existing industry-focused data science consultancy capability provided by EPCC and Mathematics to Bayes (and, later, cross-DDI) industry engagement and innovation activity and targets. 

This will enhance our capability to support 

  • Interdisciplinary industry engagement across Schools and professional services units
  • Drive AI and data science adoption through early-stage technical scoping work 
  • Support the establishment of Bayes Innovation Projects and Innovation Labs. 

The objective of the unit will be to conduct and coordinate consultancy that will result in high-impact data-driven multidisciplinary translational research and development projects across the Bayes community and beyond in support of DDI adoption and research KPIs.

The DSCU will bring together the individual strengths in doing applied technical projects available in data science, data management, high-performance computing (EPCC), statistics and operations research (School of Mathematics), complement it with additional expertise in areas such as machine learning, natural language processing, image recognition, cybersecurity, linking also with expertise in other parts of the institution (e.g. Geographical Information Systems in EDINA) to cover a wide spectrum of technical skills deployed through a small, agile team that can be rapidly deployed on industrially focused technical engagements, in close coordination with cross-unit business development activities. 

The longer-term ambition of the DSCU is to grow a new institution-wide capability which is academically connected but oriented to business development with industry partners.

Current project status

Report Date RAG Budget Effort Completed Effort to complete
May 2021 AMBER 0.0 days 0.0 days 0.0

Project Info

Project
Establish a cross-University data science consultancy community
Code
BAY213
Programme
Bayes Centre Translational Data Driven R&D (BRD)
Project Manager
Jasmina Lazic
Project Sponsor
Michael Rovatsos
Current Stage
Execute
Status
In Progress
Start Date
01-Sep-2020
Planning Date
n/a
Delivery Date
n/a
Close Date
n/a
Overall Priority
Normal

Documentation

Not available.

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