New opportunity

Research Associate (HCI, Generative AI)

National University of Singapore · Singapore

About this role

The NUS Immersive Reality Lab seeks a Research Associate to design, develop and evaluate AI-assisted exhibition tools and immersive heritage applications. The role works with curators, designers and heritage professionals to turn AI capabilities into usable systems for exhibition planning and public engagement. The position is based at Kent Ridge Campus and is open to a fixed-term contract.

Responsibilities

  • Design user-centered interaction systems and interfaces for voice and text prompting, enabling control of spatial layouts and narrative flow. Prototype interactions, conduct user studies and evaluate usability.
  • Develop prompt-driven 3D scene and gallery generation pipelines, integrate diffusion models for visualization and content generation, support text-to-scene and voice-to-scene workflows, and implement systems in real-time engines such as Unity or Unreal.
  • Build AI-assisted exhibition prototyping and visualization platforms. Develop and document end-to-end workflows covering prompt engineering, model fine-tuning and iteration, asset management and versioning, and spatial generation and annotation.

Qualifications

  • A master’s degree in HCI, Computer Science, Engineering, AI or a related field, plus at least 2 years of work experience and relevant knowledge and expertise.
  • Strong expertise in at least one of: HCI, including user studies, UX and interaction design; generative AI, including diffusion models and 3D reconstruction and rendering techniques such as Gaussian Splatting and NeRF; or immersive AR/VR/MR systems.
  • Demonstrated research capability through publications or strong project or portfolio experience, with examples including CHI, SIGGRAPH, NeurIPS, TVCG and IEEE VR.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Human-Computer InteractionGenerative AIMachine LearningUser studiesUXInteraction designUsability evaluationMultimodal promptingPrompt engineeringDiffusion models3D scene generation3D reconstructionRenderingGaussian SplattingNeRFUnityUnreal EngineModel fine-tuningAsset managementAugmented realityVirtual realityMixed reality

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A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Design and evaluate exhibition interactions

    The role calls for user-centered interfaces that let people use voice and text prompts to control spatial layouts, narrative flow, and iteration. Prototyping, user studies, and usability evaluation are explicit duties.

  • Build prompt-driven 3D workflows

    Develop scene and gallery generation pipelines, integrate diffusion models for visualisation and content generation, support text-to-scene and voice-to-scene workflows, and implement them in real-time engines such as Unity or Unreal.

  • Make the platform workflow usable and traceable

    Build AI-assisted exhibition prototyping and visualisation platforms, with documented workflows for prompt engineering, model fine-tuning and iteration, asset management and versioning, and spatial generation and annotation.

  • Translate research into heritage applications

    Collaborate with curators, designers, and heritage professionals on tools for exhibition planning and public engagement. The posting also asks for demonstrated research capability through publications or strong project or portfolio experience.

Likely challenges to think through

  • Balancing flexible prompts with predictable control

    Preparation hypothesis: voice and text input may make spatial or narrative changes hard to specify and revise precisely. Prepare to explain how you would prototype controls, observe users completing exhibition-planning tasks, and use usability findings to refine the interaction.

  • Balancing generated output with editable scenes

    Preparation hypothesis: generated visual content may not readily produce coherent, adjustable gallery layouts in a real-time engine. Prepare to discuss how you would assess outputs, handle iteration and annotations, and preserve asset versions rather than treating generation as a one-step result.

  • Aligning different professional perspectives

    Preparation hypothesis: curators, designers, and heritage professionals may value different aspects of an exhibition tool, creating trade-offs between creative flexibility and a usable planning workflow. Prepare an example of how you would elicit goals and evaluate a prototype with its intended users.

03

Practice your answers

Technical practice

How would you design a voice-and-text interface for controlling an exhibition’s spatial layout and narrative flow?

What to coverThe role calls for multimodal prompting and intuitive control of layouts, narrative flow, and iteration. Suggested preparation: explain how users would express changes, inspect the resulting state, and correct ambiguous or unintended outcomes.

How would you study whether curators can use an AI-assisted exhibition prototype effectively?

What to coverThe posting calls for prototyping, user studies, and usability evaluation. Suggested preparation: describe representative tasks, observation and feedback methods, and how findings would inform the next design iteration.

What stages would you include in a prompt-driven 3D gallery generation pipeline?

What to coverThe role includes prompt-driven scene and gallery generation, spatial generation, and annotation. Suggested preparation: trace a request through interpretation, scene construction, asset placement, annotation, and review, noting where human control is useful.

How would you handle ambiguity and errors in a voice-to-scene workflow?

What to coverThe posting explicitly includes voice-to-scene as well as text-to-scene workflows. Suggested preparation: discuss how a system could make uncertain interpretations visible and let users confirm or revise changes without losing their work.

Where would diffusion models add value in an exhibition visualization workflow, and what would you check before using their outputs?

What to coverThe role calls for integrating diffusion models for visualization and content generation. Suggested preparation: distinguish visual exploration from usable scene assets, and discuss checking output consistency and suitability for the intended exhibition context.

How would you compare NeRF and Gaussian Splatting for an immersive heritage application?

What to coverThe qualifications name both as examples of 3D reconstruction and rendering techniques; they do not require expertise in every listed specialization. Suggested preparation: compare capture assumptions, rendering performance, editability, and fit for the intended interaction.

What would you consider when bringing generated scenes into a real-time engine?

What to coverThe posting names Unity and Unreal as examples of real-time engines. Suggested preparation: discuss asset compatibility, interaction responsiveness, rendering constraints, and how you would test an iterative prototype.

How would you decide between prompt iteration and model fine-tuning when gallery outputs miss the intended result?

What to coverThe documented workflow is expected to cover prompt engineering, fine-tuning, and iteration. Suggested preparation: explain what evidence would identify the failure, what each approach might change, and how you would compare revised outputs.

How would you manage and version generated assets across exhibition design iterations?

What to coverAsset management and versioning are explicitly part of the end-to-end workflow. Suggested preparation: describe how to connect assets to prompts, model or scene revisions, annotations, and review decisions so collaborators can understand what changed.

How would you evaluate a generated exhibition scene beyond whether it renders?

What to coverThe role combines scene generation with usable systems for exhibition planning and public engagement. Suggested preparation: propose checks for spatial coherence, intended narrative flow, and whether collaborators can review and revise the result.

Behavioural practice

Tell me about a time you translated a collaborator’s domain needs into a usable prototype.

What to coverThe role involves working with curators, designers, and heritage professionals. Suggested preparation: use a real situation/action/result example that shows how you clarified needs, made design decisions, and learned whether the prototype helped.

Describe a time user-study findings changed your initial design direction.

What to coverPrototyping, user studies, and usability evaluation are stated responsibilities. Suggested preparation: give a real situation/action/result example covering the evidence you gathered, the change you made, and its observed effect.

Tell me about a time collaborators disagreed about the direction of an interactive experience.

What to coverThe role spans exhibition planning, design, and public engagement with different professional collaborators. Suggested preparation: use a real situation/action/result example to show how you surfaced the trade-off, reached a decision, and assessed the outcome.

Describe a time a research prototype failed to work as intended during an iteration.

What to coverThe posting calls for developing, evaluating, and iterating on AI-assisted tools. Suggested preparation: give a real situation/action/result example explaining how you diagnosed the issue, chose a response, and verified what improved.

Tell me about a time you documented a complex workflow so others could build on it.

What to coverDeveloping and documenting end-to-end workflows is a stated responsibility. Suggested preparation: use a real situation/action/result example showing what needed to be reproducible, how you organized the documentation, and how others used it.

02

Sharpen your knowledge

Topics to prepare

  • User-centered HCI research

    Review how to turn curator and visitor needs into interaction goals. Exercise: outline a user study for an exhibition-planning interface, including tasks, observations and usability measures. The posting explicitly calls for user-centered design, user studies and usability evaluation.

  • Multimodal control of exhibitions

    Compare how voice and text prompts could control spatial layout, narrative flow and iterative edits. Exercise: map one exhibition request to possible interface actions and identify where a user should confirm or revise the result. These controls are named responsibilities.

  • Generative 3D and visualization concepts

    Review prompt-driven scene generation and diffusion-model visualization; compare where Gaussian Splatting and NeRF fit as reconstruction and rendering techniques. Exercise: sketch a text-to-scene pipeline and explain its likely limitations. The posting names these approaches, while requiring strong expertise in at least one of HCI, generative AI/3D, or immersive systems.

  • Immersive-system design

    Compare AR, VR and MR considerations for presenting heritage content. Exercise: critique a proposed immersive gallery experience for spatial clarity and interaction usability. Immersive applications are part of the role, and immersive systems are one of the listed expertise areas.

  • Research contribution and evidence

    Exercise: take one relevant publication or project and summarize its question, method, findings and limitations. The posting seeks demonstrated research capability through publications or strong project or portfolio experience.

Skills to revise

  • Prototype voice and text interactions

    Build a small interface mock-up that accepts a voice or text instruction to change a gallery layout, then supports a follow-up edit. This practices the posting's multimodal prompting and iterative spatial-control work.

  • Run a focused usability evaluation

    Write tasks for a curator using the mock-up, conduct a small practice session and record where instructions or generated results cause confusion. Prototyping, user studies and usability evaluation are explicit responsibilities.

  • Assemble a prompt-to-scene workflow

    Create a small, illustrative gallery scene from a text prompt, document how generated content becomes spatially placed assets, and test one revision. This targets the stated prompt-driven 3D scene and gallery pipelines; it is a preparation exercise, not a specified employer project.

  • Integrate a scene in a real-time engine

    Use either Unity or Unreal to display and revise a simple gallery layout, noting how assets and annotations are represented. The posting calls for implementation in real-time engines and spatial generation and annotation.

  • Document and version an iteration

    Record a prompt, output, asset versions, an annotation change and the reason for a subsequent revision. This rehearses the specified end-to-end workflow covering prompt engineering, model iteration, asset management and versioning.

04

Your preparation checklist

  • Organize qualification evidence

    Prepare a one-page map of your degree, relevant work experience, strongest area of expertise, and publications or portfolio projects. The posting asks for a relevant master’s degree, at least two years of work experience, and demonstrated research capability.

  • Prepare a project walkthrough

    Choose a relevant HCI, generative AI, or immersive-systems project. Be ready to explain the problem, your contribution, implementation choices, evaluation, and limitations; connect it to exhibition planning or public engagement where applicable.

  • Outline a multimodal interaction study

    Draft a brief study plan for voice and text controls over gallery layout or narrative flow. Specify intended users, prototype tasks, usability measures, and how findings would inform iteration; these activities reflect the posted HCI responsibilities.

  • Sketch a scene-generation design

    Prepare a clearly labeled proposed design for a prompt-to-3D-gallery workflow, covering text and voice input, generation or visualization, and a Unity or Unreal implementation. Identify technical uncertainties rather than presenting the design as an existing system.

  • Document an end-to-end workflow

    Create a workflow diagram showing prompts, model iteration or fine-tuning, asset versioning, and spatial annotation. The posting names these platform-development tasks; note where curators or designers would review outputs.

  • Prepare collaboration examples and questions

    Identify an example of working with nontechnical stakeholders, if available. Bring questions about curator workflows, how prototypes are evaluated, and priorities for exhibition planning versus public engagement; the posting describes collaboration but does not specify these details.

AI-generated from the job information · Prepared Sep 30, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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