Job Description

Ref Number

B04-06733

Professional Expertise

Teaching, Teaching Support and Examination Support

Department

UCL BEAMS (B04)

Location

London

Working Pattern

Full time

Salary

54,931-64,644

Contract Type

Fixed-term

Working Type

Hybrid

Available for Secondment

Yes

Closing Date

17-Nov-2025

About us

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In the Institute for Sustainable Heritage we deliver sustainable solutions to real-world cultural heritage problems through ground-breaking, cross-disciplinary research and innovative teaching for future heritage leaders. Since 2019, our MSc Sustainable Heritage was the first in the sector to include Data Science, and the module "Machine Learning for Heritage" is the cornerstone of this teaching project.

About the role

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The main purpose of the job is to lead and deliver the Module BENV0115: Machine Learning for Heritage.


The module takes place on Mondays and Fridays of Term 2, 9-12, in Bloomsbury. It is attended by approximately 30 students. It is evaluated with a report. The module has already been fully designed and delivered three times in its current form, so there are prepared slides, lecture recordings and coding exercises in Python (in Google Colab). The post-holder can deliver the module as-is or modify it creatively if they wish, in conversation with Prof. Josep Grau-Bove and the programme lead, Dr. Pakhee Kumar. For example, students are very interested in hearing about original research, so you are welcome to develop a lecture on your own work. The module covers linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks and deep learning. The module includes some domain knowledge of heritage but this is not examinable and therefore not an essential requirement of candidates. The post-holder will also contribute to teaching and delivery of the MSc Sustainable Heritage, including supervision and marking. These requirements are flexible and can be agreed depending on the FTE and the length of the role.




This post is available from 12 January 2026 and is funded until 30 April 2026 in the first instance; further funding to support the post may become available.



A job description and person specification can be accessed at the bottom of this page.



If you have any queries regarding the vacancy, or the application process, please contact bseer-recruitment@ucl.ac.uk.



If you have specific questions about the role please contact Josep Grau-Bove, josep.grau.bove@ucl.ac.uk



UCL welcomes applications from international applicants and has licence to sponsor individuals who require a visa. This is dependent on the post and candidate meeting eligibility requirements for visa sponsorship under UK Visas and Immigration legislation.

About you

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We are looking for a candidate with a PhD in a technical topic and research experience using machine learning in real world settings. Experience using Python for machine learning is essential. The ideal applicant will also have experience in postgraduate teaching. An interest in heritage is desirable, but not essential: this is predominantly a machine learning and data science module, with heritage as an area of application.

What we offer

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As well as the exciting opportunities this role presents, we also offer some great benefits, some of which are below:


41 Days holiday (27 days annual leave, 8 bank holiday and 6 closure days) Additional 5 days' annual leave purchase scheme Defined benefit career average revalued earnings pension scheme (CARE) Cycle to work scheme and season ticket loan Immigration loan Relocation scheme for certain posts On-site nursery On-site gym Enhanced maternity, paternity and adoption pay Employee assistance programme: Staff Support Service Discounted medical insurance

Visit https://www.ucl.ac.uk/work-at-ucl/rewards-and-benefits to find out more.

Our commitment to Equality, Diversity and Inclusion

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As London's Global University, we know diversity fosters creativity and innovation, and we want our community to represent the diversity of the world's talent. We are committed to equality of opportunity, to being fair and inclusive, and to being a place where we all belong. We therefore particularly encourage applications from candidates who are likely to be underrepresented in UCL's workforce. These include people from ethnic minority backgrounds; disabled people; LGBTQI+ people; and for our Grade 9 and 10 roles, women. Our department holds an Athena SWAN Silver award in recognition of our commitment and demonstrable impact in advancing gender equality.