Fully Funded PhD Research Studentship

Fully Funded PhD Research Studentship

Reference: REQ001796

Job details

Job referenceREQ001796 Date posted23/09/2026 Application closing date31/10/2026 LocationDundee SalaryTax-free stipend of £21,805 Contractual hours35 BasisFull time Job category/typeDesign, Informatics and Business Attachments Blank

Fully Funded PhD Research Studentship

Job description

Fully Funded PhD Research Studentship

Project Title: AI-Augmented Procedural Node-Graph Authoring for Technical Artists

PhD Studentship: R-LINCS2 funded. The Studentship is available for a February start.

A PhD studentship that comprises tax-free stipend of £21,805 (increasing in line with UKRI per annum), tuition fees paid, and a generous study package (e.g., limited research consumables, travel budget, and training when appropriate) each year for 3 years. The studentship is fully funded for 3 years. An extension of funding for a further 6 months is available, contingent upon the candidate completing 70 hours of teaching per year during the initial 3 years.

The pan-University Graduate School offers an integrated training programme to the postgraduate community within a single centre, serving to inculcate interdisciplinary working in our next generation of researchers.

Interviews are likely to be online in November.

Project Description: Procedural node-based systems such as Houdini give technical artists transparent, reproducible and fully editable control over modelling, animation, visual effects and compositing. Building these systems requires considerable expertise and can be repetitive, as each task may involve constructing or adapting large networks of nodes and parameters. This practice-based PhD investigates how AI can assist at the level of tool production by drafting procedural networks that the experienced technical artist can inspect, modify and extend.

The project will explore a range of AI predictive and generative methods, such as large language and vision models (LLMs/VLMs), inverse procedural modelling, Bayesian optimisation, world models and neural simulation. These methods will be used to develop an AI-augmented framework that can translate an artist-led brief into an executable build script. Houdini is proposed as the initial development environment. Within Houdini, the script would construct a native node network using standard operators, set initial parameters and add new parameters that expose meaningful artistic controls. The ‘network builder’ will produce editable procedural networks rather than final scenes or images. The experienced technical artist would remain responsible for the creative direction, adjusting parameters and refining and extending the network.

Key project objectives:

1. Investigating AI-augmented procedural authoring: explore how AI methods can translate artwork-led briefs into editable procedural node networks.
2. Developing a working network building tool: create a prototype that generates native node networks and exposes meaningful artist controls.
3. Evaluating technical and creative use: evaluate the prototype through technical testing and creative practice, focusing on functionality, editability and creative control and agency.

 The project offers potential alignment with CoSTAR and its research into virtual production and real-time technologies. In this context, the Network Builder could support the rapid creation and adaptation of procedural assets, effects and visual systems.  More broadly, the project has potential applications within film, games, animation and visual-effects production pipelines, where procedural networks are routinely built and adapted for new creative tasks. Although Houdini provides the initial context, the underlying approach may also be applicable to other node-based systems. Findings would be shared with academic and industry audiences through publications, presentations and demonstrations of the prototype.

Supervisory Team: The candidate will be supervised within the Division of Games Technology and Mathematics by Dr Paul Goodfellow, Dr Javad Zarrin and Dr Thomas Howson. Queries on this project should be directed to Dr Paul Goodfellow ([email protected]).

Entry Requirements: Candidates must have, or expect to obtain, a first-class or upper second-class honours degree in technical art, creative computing, computer science or AI, games technology, animation/VFX or a related discipline.

We are looking for an independent, enthusiastic and driven candidate with experience in at least one of the following areas: procedural or node-based production, AI or machine learning, or technical art. Applicants should have demonstrable programming or scripting experience and the ability to develop and evaluate working software prototypes. Python is essential, and Houdini’s VEX is also relevant to the project. Experience with other suitable languages will also be beneficial. Candidates should have an interest in working across technical development and creative practice. Experience with Houdini or another procedural digital content creation environment is desirable.

For applicants who are non-native speakers of English, the University requires IELTS of 7.0 (with no band less than 6.5) or an equivalent qualification accepted by the Home Office.

Applications and closing date: 31/10/2026

Applicants should submit through the Abertay University jobs page https://www.abertay.ac.uk/about/working-at-abertay/jobs/, submitting a personal statement of application detailing why you are interested in undertaking this project, and a CV.

If you are selected for interview you will be required to complete an online Research Student Application Form which includes the submission of a research proposal. Guidance on how to write the proposal can be found here: https://www.abertay.ac.uk/study-apply/how-to-apply/how-to-apply-postgraduate-research/ Applicants are strongly encouraged to contact Dr Paul Goodfellow ([email protected]) for advice on developing a proposal prior to submitting it.

Abertay is a small, modern University renowned for working across traditional research boundaries, pioneering in new and emerging disciplines and sectors. It was named one of the top 3 Modern Universities in the UK for Research Intensity by the Complete University Guide 2024.

According to the results of the Research Excellence Framework 2021, Abertay recorded 60% of its research judged as 'internationally excellent' or 'world-leading', a 23% increase since the last REF2014 – the biggest climb of any Scottish university. The University is committed to the principles outlined in the Vitae Researcher Development Framework and the Concordat to support the Career Development of Researchers.  Abertay postgraduate students are hosted in our vibrant, multidisciplinary https://www.abertay.ac.uk/schools/graduate-school/ Graduate School, designed to promote integration and collaborative working. You will be supported by expert supervision and an exceptional research environment. Abertay offer an extensive training and professional development program to enhance research excellence, impact and individual employability.

 Abertay University recently opened a new Competitive Games Lab, a dedicated research facility partly funded by the Dundee City Council through the UK government’s Shared Prosperity Fund.

 We hold an Athena SWAN Institutional Bronze award and were the first Scottish University to achieve the Race Equality Charter Mark.

 Entry requirements

Essential requirements:	Desirable requirements (but not essential)
First class or upper second-class honours degree in technical art, creative computing, computer science or AI, games technology, animation/VFX or a related discipline.	Masters level qualification in a relevant discipline
Demonstrable experience in at least one of the following areas: procedural or node-based production, AI or machine learning, or technical art.	Demonstrable experience with Houdini, VFX and VEX
Demonstrable programming or scripting experience with Python	Experience using Python and/or VEX for procedural or technical-art workflows.
The ability to develop, test and evaluate working software prototypes.	Practical experience with relevant AI or machine-learning models, libraries or APIs.
The ability to undertake independent research, critically evaluate findings and communicate technical and creative ideas clearly.	Experience developing procedural tools, node-based systems or other forms of technical-art tool development and implementation.
Applicants who are non-native speakers of English, the University requires IELTS of 7.0 (with no band less than 6.5) or an equivalent qualification accepted by the Home Office

If you believe you have the skills and experience for this exciting and challenging role, please submit your application by clicking apply online below.

Apply online Send to a friend

Fully Funded PhD Research Studentship

Job description

Fully Funded PhD Research Studentship

Project Title: AI-Augmented Procedural Node-Graph Authoring for Technical Artists

PhD Studentship: R-LINCS2 funded. The Studentship is available for a February start.

A PhD studentship that comprises tax-free stipend of £21,805 (increasing in line with UKRI per annum), tuition fees paid, and a generous study package (e.g., limited research consumables, travel budget, and training when appropriate) each year for 3 years. The studentship is fully funded for 3 years. An extension of funding for a further 6 months is available, contingent upon the candidate completing 70 hours of teaching per year during the initial 3 years.

The pan-University Graduate School offers an integrated training programme to the postgraduate community within a single centre, serving to inculcate interdisciplinary working in our next generation of researchers.

Interviews are likely to be online in November.

Project Description: Procedural node-based systems such as Houdini give technical artists transparent, reproducible and fully editable control over modelling, animation, visual effects and compositing. Building these systems requires considerable expertise and can be repetitive, as each task may involve constructing or adapting large networks of nodes and parameters. This practice-based PhD investigates how AI can assist at the level of tool production by drafting procedural networks that the experienced technical artist can inspect, modify and extend.

The project will explore a range of AI predictive and generative methods, such as large language and vision models (LLMs/VLMs), inverse procedural modelling, Bayesian optimisation, world models and neural simulation. These methods will be used to develop an AI-augmented framework that can translate an artist-led brief into an executable build script. Houdini is proposed as the initial development environment. Within Houdini, the script would construct a native node network using standard operators, set initial parameters and add new parameters that expose meaningful artistic controls. The ‘network builder’ will produce editable procedural networks rather than final scenes or images. The experienced technical artist would remain responsible for the creative direction, adjusting parameters and refining and extending the network.

Key project objectives:

1. Investigating AI-augmented procedural authoring: explore how AI methods can translate artwork-led briefs into editable procedural node networks.
2. Developing a working network building tool: create a prototype that generates native node networks and exposes meaningful artist controls.
3. Evaluating technical and creative use: evaluate the prototype through technical testing and creative practice, focusing on functionality, editability and creative control and agency.

 The project offers potential alignment with CoSTAR and its research into virtual production and real-time technologies. In this context, the Network Builder could support the rapid creation and adaptation of procedural assets, effects and visual systems.  More broadly, the project has potential applications within film, games, animation and visual-effects production pipelines, where procedural networks are routinely built and adapted for new creative tasks. Although Houdini provides the initial context, the underlying approach may also be applicable to other node-based systems. Findings would be shared with academic and industry audiences through publications, presentations and demonstrations of the prototype.

Supervisory Team: The candidate will be supervised within the Division of Games Technology and Mathematics by Dr Paul Goodfellow, Dr Javad Zarrin and Dr Thomas Howson. Queries on this project should be directed to Dr Paul Goodfellow ([email protected]).

Entry Requirements: Candidates must have, or expect to obtain, a first-class or upper second-class honours degree in technical art, creative computing, computer science or AI, games technology, animation/VFX or a related discipline.

We are looking for an independent, enthusiastic and driven candidate with experience in at least one of the following areas: procedural or node-based production, AI or machine learning, or technical art. Applicants should have demonstrable programming or scripting experience and the ability to develop and evaluate working software prototypes. Python is essential, and Houdini’s VEX is also relevant to the project. Experience with other suitable languages will also be beneficial. Candidates should have an interest in working across technical development and creative practice. Experience with Houdini or another procedural digital content creation environment is desirable.

For applicants who are non-native speakers of English, the University requires IELTS of 7.0 (with no band less than 6.5) or an equivalent qualification accepted by the Home Office.

Applications and closing date: 31/10/2026

Applicants should submit through the Abertay University jobs page https://www.abertay.ac.uk/about/working-at-abertay/jobs/, submitting a personal statement of application detailing why you are interested in undertaking this project, and a CV.

If you are selected for interview you will be required to complete an online Research Student Application Form which includes the submission of a research proposal. Guidance on how to write the proposal can be found here: https://www.abertay.ac.uk/study-apply/how-to-apply/how-to-apply-postgraduate-research/ Applicants are strongly encouraged to contact Dr Paul Goodfellow ([email protected]) for advice on developing a proposal prior to submitting it.

Abertay is a small, modern University renowned for working across traditional research boundaries, pioneering in new and emerging disciplines and sectors. It was named one of the top 3 Modern Universities in the UK for Research Intensity by the Complete University Guide 2024.

According to the results of the Research Excellence Framework 2021, Abertay recorded 60% of its research judged as 'internationally excellent' or 'world-leading', a 23% increase since the last REF2014 – the biggest climb of any Scottish university. The University is committed to the principles outlined in the Vitae Researcher Development Framework and the Concordat to support the Career Development of Researchers.  Abertay postgraduate students are hosted in our vibrant, multidisciplinary https://www.abertay.ac.uk/schools/graduate-school/ Graduate School, designed to promote integration and collaborative working. You will be supported by expert supervision and an exceptional research environment. Abertay offer an extensive training and professional development program to enhance research excellence, impact and individual employability.

 Abertay University recently opened a new Competitive Games Lab, a dedicated research facility partly funded by the Dundee City Council through the UK government’s Shared Prosperity Fund.

 We hold an Athena SWAN Institutional Bronze award and were the first Scottish University to achieve the Race Equality Charter Mark.

 Entry requirements

Essential requirements:	Desirable requirements (but not essential)
First class or upper second-class honours degree in technical art, creative computing, computer science or AI, games technology, animation/VFX or a related discipline.	Masters level qualification in a relevant discipline
Demonstrable experience in at least one of the following areas: procedural or node-based production, AI or machine learning, or technical art.	Demonstrable experience with Houdini, VFX and VEX
Demonstrable programming or scripting experience with Python	Experience using Python and/or VEX for procedural or technical-art workflows.
The ability to develop, test and evaluate working software prototypes.	Practical experience with relevant AI or machine-learning models, libraries or APIs.
The ability to undertake independent research, critically evaluate findings and communicate technical and creative ideas clearly.	Experience developing procedural tools, node-based systems or other forms of technical-art tool development and implementation.
Applicants who are non-native speakers of English, the University requires IELTS of 7.0 (with no band less than 6.5) or an equivalent qualification accepted by the Home Office

If you believe you have the skills and experience for this exciting and challenging role, please submit your application by clicking apply online below.

Apply online Send to a friend