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Research Fellow (Generative AI and 3D Scene Generation)

MyCareersFuture92,121 open roles

Pay
SGD 5,800 – SGD 6,500 a month
Where
West, Singapore
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Your applicationOpen nowResearch Fellow (Generative AI and 3D Scene Generation)MyCareersFuture · West, Singapore
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The posting

Interested applicants are invited to apply directly at the NUS Career Portal. Please note your application will only be processed if you apply via NUS Career Portal.

NUS Career Portal link - https://careers.nus.edu.sg/job/Research-Fellow-%28Generative-AI-and-3D-Scene-Generation%29/34570-en_GB/

We regret that only shortlisted candidates will be notified.

Job Description

The Immersive Reality Lab at NUS is looking for a Research Fellow in generative AI and 3D content to join the project "Immersive Technologies for Heritage Engagement and Preservation". You will lead the technical development of AI-assisted tools that help curators and designers plan, visualise and prototype exhibitions, and that bring heritage content to the public through immersive experiences. You will join a multidisciplinary team of full-time researchers, engineers and designers in the lab, and work with curators, designers and heritage professionals from our partner institutions. The aim is to turn current generative AI and 3D capabilities into working systems that people in the heritage sector can actually use. You may also contribute to the lab's other projects, such as those in healthcare and aviation.

Key Responsibilities 1. Generative AI and 3D pipelines • Design and build pipelines that generate 3D scenes and gallery layouts from text, voice or reference images • Integrate and adapt diffusion models and other generative models for visualisation and content creation • Apply 3D reconstruction and rendering methods (e.g. Gaussian Splatting, NeRF, photogrammetry) to digitise heritage objects and spaces • Fine-tune and test models on heritage collections, paying attention to accuracy, provenance and cultural sensitivity

2. Platform and system development • Build an AI-assisted exhibition prototyping and visualisation platform in a real-time engine (Unity or Unreal), with AR/VR/MR deployment where relevant • Develop and document end-to-end workflows covering prompt design, model fine-tuning and iteration, asset management and versioning, and spatial generation and annotation • Keep the system reliable enough for pilot deployments with partners

3. Research and dissemination • Define technical research questions and benchmark the system on generation quality, speed and controllability • Work with lab colleagues on iterative testing with curators and visitors, and act on what the studies show • Publish in leading venues and contribute to demos, technical reports and project deliverables • Guide research engineers and student interns on the technical work

About the NUS Immersive Reality Lab The Immersive Reality Lab at the College of Design and Engineering, National University of Singapore (NUS), does research where augmented, virtual and mixed reality (AR/VR/MR), artificial intelligence (AI) and human-computer interaction (HCI) meet. Our work is translational. We partner with industry and public sector organisations in healthcare, aviation and cultural heritage, and take research out of the lab into real-world use. Funding is available for two years. The initial contract is for 12 months and is renewable subject to performance.

Qualifications

Qualifications • PhD in Computer Science, Computer Engineering, AI, HCI or a related field Required experience and skills • Strong expertise in at least one of the following, and working knowledge of the other: 1. Generative AI (e.g. diffusion models) and 3D reconstruction or neural rendering (e.g. Gaussian Splatting, NeRF) 2. Immersive systems development (AR/VR/MR) in Unity or Unreal • Solid programming skills in Python and C# or C++, with hands-on experience training or fine-tuning deep learning models • A record of research output, such as publications at venues like CHI, SIGGRAPH, NeurIPS, CVPR, IEEE VR or TVCG, or a strong portfolio of systems you have built • Able to work with non-technical collaborators and explain technical trade-offs clearly

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