Who can nominate: Self-nominations and nominations by others are equally welcome. For those in leadership roles, please encourage and support others to apply.

Award for each prize: Certificate + Gift voucher (one prize per category).

Inclusive Selection Process: Applications from individuals from underrepresented and underserved backgrounds are particularly encouraged, and special consideration will be given to applicants who have faced systemic barriers in academia. Additional time will be allowed for career breaks. A wide variety of reasons will be recognised. For parental leave, we allow 18 months per child for birthing parents, 6 months per child for non-birthing parents by default, but please state if a longer duration is required.

Submissions details:

· Closing date: 17:00, Monday 1 December 2025

· What to include: 1 x Short CV (max 2 pages) and 1 x Statement explaining how the applicant addresses the criteria for the award (max 2 pages)

· (Optional): Provide any further details relevant to your application. This section is optional and can be up to 200 words. You should not use it to describe additional skills, experiences, or outputs, but you can use it to describe any factors that provide context for the rest of your application (for example, details of career breaks if you wish to disclose them).

· Submitting: Documents to be emailed to:dsi@lancaster.ac.uk

1. Early Career Researcher Award

This award recognises exceptional academic contributions to data science and AI by researchers who are in the early stages of their careers.

Eligibility:

• Researchers within 5 years of completing their PhD (or equivalent).
• Current members of DSI and DSI alumni who left LU <12 months before the closing date.
• Actively engaged in academic research in data science, AI, or related fields.

Assessment Criteria:

• Research Innovation: Demonstrated contributions to innovative, high-impact research in data science or AI.
• Mentorship and Collaboration: Active engagement with the data science and AI community (formal or informal), including advocacy that creates opportunities for researchers and support for underrepresented groups.
• Potential for Growth: Clear potential to make lasting, positive contributions to the academic community.

2. Diversity in Data Science Champion Award

This award celebrates academic researchers, faculty, or research teams who have made outstanding contributions to diversity, equity, and inclusion within data science and AI, with a focus on creating pathways for historically underrepresented and underserved groups.

Eligibility:

• Open to researchers, faculty, or teams.
• We are looking for individuals or teams that embed diversity, inclusion, and equity in their academic work and/or actively foster these values within their team and beyond through community engagement.

We note the potential diversity of contributions. Applications should address at least one of the following, as relevant to your specific contribution.

Indicative Assessment Criteria:

• Leadership in Inclusivity: Demonstrated efforts to create inclusive academic spaces for historically underrepresented or underserved groups in data science and AI.
• Institutional Change: Evidence of driving institutional or structural change that supports diversity, equity, and inclusion.
• Mentorship & Advocacy: Active involvement in mentorship or advocacy programs that support underrepresented or underserved students and early-career researchers in data science or AI.
• Community Engagement: Efforts to collaborate with or serve underrepresented communities within or outside of academia.

3. Excellence in Data Science & AI

This award recognises individuals who have demonstrated outstanding academic contributions to data science and AI, with priority given to those who have promoted inclusivity and supported underrepresented communities.

Eligibility:

• Open to members of DSI who are >5 years out of their PhD.

Indicative Assessment Criteria:

• Research Excellence & Impact: A record of impactful, high-quality research in data science or AI with evidenced contributions to the academic community and beyond.
• Educational Leadership: Contributions to developing inclusive educational practices, mentoring, and fostering diverse talent in data science and AI.
• Broader Community Influence: Recognition of the individual’s role in shaping the field in a way that includes and elevates underrepresented voices and perspectives.