GLIGE (www.glige.co.uk) is an early-stage start-up focused on developing AI Generative Design to industrialise construction. We aim to revolutionise how buildings and infrastructure are designed, manufactured and delivered by developing advanced AI generative design models.
As a growing organisation, GLIGE offers the chance to help shape its technology, culture, and product strategy from the start. A mix of salary and equity can be awarded for the right candidate.
Role Description
We are seeking an AI scientist to co-lead the design, development, and deployment of an AI generative design system for the industrialisation of construction. On a day-to-day basis, you will architect core Graph-based (GNN) and PDE-based (PNN) AI models, build and iterate early AI prototypes at speed, and translate early users’ feedback into technical roadmaps.
Qualifications
- Experience with Graph AI models, including Graph Neural Networks, and/or Physics-constrained neural networks, including Partial Differential Equations, demonstrated through research publications or direct working experience.
- Passion and desire to resolve real-world problems, not just research. Industry expertise is less relevant (construction or pharma/Clinical).
- Exceptional coding skills with a strong command of modern software practice, including PyTorch.
- A PhD in a relevant field (Computer Science, Physics, Applied Mathematics, Machine Learning, Computational Science) with a strong foundation in GNN, Diffusion models and PDE. A Master’s in the above discipline with 3-7 years of direct work experience on GNN, Diffusion models and physics-informed neural networks can be considered.
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