Supported by the Tay Cities Partnership, Data Skills for Work at The Data Lab is offering eligible training and education providers funding to deliver data skills training for learners in our target groups as part of an integrated and inclusive pipeline of development.
The maximum grant is £12,000 per course for a minimum of 20 learners, the minimum is £6,000 for a minimum of 10 learners (training must be free at the point of access to those learners). The grant will be administered by The Data Lab (TDL) through The University of Edinburgh. Courses can be delivered multiple times (and therefore applicants can apply to deliver more than one course), but all courses must be completed by 31st March 2026.
A limited number of places are available for ESES learners. Providers wishing to include these should specify in their application whether they intend to target Tay Cities only, or both Tay Cities and ESES regions.
The Data Lab is publicly funded and therefore these grants will constitute a state funded subsidy where the organisation receiving the funding is classed as an “enterprise” under the Subsidy Control Act 2022. The Subsidy Control Act 2022 permits enterprises to lawfully receive subsidies up to a total value of £315,000 over the period consisting of the elapsed part of the current financial year, and the two financial years immediately preceding the current financial year period (the “Minimum Financial Assistance Cap”). Where an organisation offered funding is an enterprise under the Subsidy Control Act 2022, the organisation will be required to confirm that its receipt of such funding shall not cause it (together with any organisation forming part of the same enterprise) to exceed the Minimum Financial Assistance Cap. Before applying, you must ensure, where applicable, you will be able to provide such confirmation.
Once we have reviewed your application, we will be in touch to let you know if your application has been successful, and if so, to provide you with our Provider Agreement for your review. Please note that any awards of funding will be subject to agreeing and signing our Provider Agreement.
Privacy
We are committed to protecting and respecting your privacy. Please read our privacy notice for full details of how we will use your information
Please review the call guidance before submitting an application.
Applications close on Monday 14th November at 5pm.
Host Organisation Guidelines for a Successful Placement
In order to ensure that both Host Organisations and TDL Academy students have the best possible experience during the Placement Programme, we ask all participating organisations to agree to the following set of rules and regulations which follow ‘best practice’ guidelines.
We understand that employers will be operating in a number of different ways in regards to remote/hybrid working. If working mainly remotely, the student will be required to be in regular contact with the host organisation during placement (daily if required) and must be provided with access to the data and any specialist equipment required to deliver the project.
If the project requires the student to work mainly/full-time in the office and remote work is not feasible please provide this detail when submitting your project form. It is our duty to ensure that students are working in a safe manner at all time and are comfortable with the expectations in relation to work location.
1. All students must be employed by the Host Organisation and paid for their time working on this Project at a minimum of the Real Living Wage.
2. The student’s terms and conditions of working and working pattern will be agreed prior to commencement of employment, in line with the Host Organisation’s normal HR processes. This is usually 35-40 hours.
3. Project duration is normally 8-12 weeks and we ask that you bear in mind the submission date of the student’s academic dissertation. Please try to allow sufficient time for writing up on an ongoing basis and we advise that the project should end at least 2 weeks before the student’s submission date.
The duration of the project and time allowed for write up must be agreed with the student and academic supervisor prior to commencement.
4. Timing of placements: for most full-time students this will be May – August. Some part-time students may wish to start their projects earlier in the year or continue into the Autumn, if this is feasible.
5. Any background checks, on-boarding, etc must be started as soon as the student has been identified and offered the Project. Please ensure any stakeholders (including external service providers) in this process are aligned as soon as possible and that the checks can be completed well in advance of the student’s start date.
6. An industrial supervisor/s should be identified (preferably a permanent member of staff) prior to the placement commencing. The student will also have an academic supervisor who will liaise with the industrial supervisor and the student. There should also be regular meetings (at least monthly, although preferably weekly/biweekly) with the industrial supervisor, academic supervisor and student.
7. All technology and data resources for the Project should be sourced and accessible from the first day of student starting with your organisation. Delays in providing these resources will result in project delays which can seriously impact the student’s ability to complete the project and their dissertation.
8. Any IP agreements/restrictions and/or NDA requirements should be discussed and resolved before the placement commences. IP normally resides with the company with the stipulation that the student has access to the elements required to complete their dissertation. The academic supervisor will be the main point of contact on IP and NDA issues.
9. Any concerns over the Project or the students’ performance must be raised, in writing, immediately with the student’s academic supervisor. If these concerns are not addressed satisfactorily by the academic supervisor, this should be escalated at the earliest opportunity in writing to the Placements team at The Data Lab. You will receive contact from The Data Lab before, during and after the placement to check on progress and provide support.
10. Should the student be offered further employment by your organisation within 12 months of the placement completion, a fee will be incurred payable directly to The Data Lab:
- Public sector organisations, third sector organisations, & partners of The Data Lab – £0
- Start-ups – £1000
- Private sector SMEs – £2500
- Private sector Other – £5000
The Data Lab reserve the right to amend these fees at their discretion. Income generated from fees is not for profit and will be used to further develop and sustain The Data Lab Academy Programme, enable the continuation of scholarship funding and industry placements in the future. If the student leaves the role within the first 3 months of further employment, your organisation will be eligible for a full rebate of the fee.
11. The Host Organisation agrees to provide all information and assistance as reasonably required by The Data Lab for the purposes of The Data Lab assessing the success of the programme, promoting the programme or as required for reporting to its funders, this shall include but is not limited to, the provision of a case study in relation to the Project.
12. For further information about how we use personal data including contact details, please see our privacy policy. The information submitted via the Project form will be stored on a third party platform for the purposes of matching, but no personal data will be transferred.
The Data Lab Academy (TDL) Masters Scholarship Programme - Funding Call for Academic Year (AY) 2026/27
Scottish Universities are invited to apply to join our Masters Scholarship Programme. The scholarships are for students studying masters courses in data, AI and related subjects across Scotland. We cover fees and students join our highly regarded programme of events which complements their academic studies with real-world employability training, industry engagement, and access to a vibrant community of peers and professionals. The funding is provided by The Scottish Funding Council and so eligibility restrictions apply.
We currently support students studying at 13 Universities on 35 different masters courses. You can find the list of approved courses for AY 25/26 here.
The masters programme consists of around 50 hours of training spread across the academic year and is a combination of online and in-person activities including:
- employability training and optional paid industrial placement in Scotland;
- an industry-led residential Innovation Challenge;
- an Interactive master class on Bias in AI and other themed activities;
- access to a network of expertise through The Data Lab MSc Alumni, The Data Lab Community and The Data Lab partners including Scottish Government, IBM and Wheatley Group; and
- a Masters Programme Certificate of Completion.
Context
In 2025 The Data Lab published its Data & AI Framework. This Framework explains the skills and competencies needed to thrive in a data-driven world and is informed by our research on the data and AI skills gap in Scotland. Its findings underpin activities across the masters programme. The Framework is defined across four Data and AI personas, which align with levels of data literacy in key competency areas: Data & AI Citizen; Data & AI Worker; Data & AI Professional and Data & AI Leader.
The Masters programme operates at the Data & AI Professional persona level where an advanced level of data literacy and expertise in advanced analytics, machine learning, and data governance is expected. We will be using the defined competencies for this persona to assess the suitability for masters courses to join our programme.
Apply to join/continue
We invite existing and new academic partners to apply to join the programme. Applications should demonstrate how their masters courses will deliver the defined competencies for a Data & AI Professional across the following areas: Data Literacy, Programming, Machine learning, Data & AI ethics, Data management, Cybersecurity and Meta-skills. We will ask you to indicate the competency levels that students on your course will achieve at the end of the course using the Framework. We also ask about the roles your course is preparing students for post graduation. This is to ensure that the courses we fund are meeting the demands of industry and support a confident, inclusive, and future-ready workforce.
We will prioritise applications for courses with a strong focus on data management and engineering, AI, software engineering and computer science. We also welcome related courses eg data analytics, business analytics and STEM data orientated courses, or specialist courses which are driving innovation in their field. All applications should demonstrate innovation and creativity in course delivery; high standards and the teaching of data ethics; a commitment to maximising diversity in applicants; strong industry engagement; and support of the Scholarship placement opportunity.
We will consider in-person, on-line or hybrid courses. Irrespective of mode of study, all students are required to attend our programme of events and meet SFC eligibility criteria.
Course Review Process: The course review and allocation process will remain the same as in previous years, with successful universities awarded scholarship numbers to select the best candidates for their course.
Student Application Process: We ask that potential scholarship candidates are identified by universities complete a short application form for review and approval by TDL prior to scholarships being confirmed with students.
Eligibility: Students must meet the SFC eligibility criteria. Refer to this SAAS advice for guidance on who can be considered for funded scholarships.
Scholarships available: Around 100 scholarships will support £6800 per student to cover MSc course tuition fees on approved courses for the AY 26-27. Any shortfall between the University’s tuition fee and the £6800 scholarship must be met by the University, and not by the student or any other third party. All students join the Masters programme.
Next steps
- Apply using this form. The closing date for applications is Friday 16th January 2026 at 18:00.
- Universities will be notified of the success or otherwise of their application by Friday 30th January 2026.
- Please contact The Data Lab at TDL-Academy@thedatalab.com if you would like an informal discussion about our programme or our eligibility requirements prior to applying.
This form is to update The Data Lab on the progress of the Industrial Doctorate project.
We will prompt you to complete this form after every 6 months.
The Data Lab (administered from The University of Edinburgh) may share information about projects with the Scottish Funding Council, Scottish Government, Scottish Enterprise, Highlands and Islands Enterprise and any other appropriate organisation in the interests of developing and promoting the Innovation Centres Programme.