Spatial Computing and Artificial Intelligence Engineer (KTP Associate)

University of Essex; Rayleigh; On-site; GBP 29,000 - 36,000; Full time

Job summary

The University of Essex, in partnership with Railscape Limited, invites applications for a graduate to develop an intelligent 3D visualization platform that provides personalised, accessibility-aware 3D walkthroughs of rail stations and other sites using spatial computing and AI.

You will work on 3D mapping, Gaussian Splat models, and ML-based object detection, while embedding conversational AI for location-aware route suggestions.

Qualifications

• Master’s degree in AI/CS/Robotics or related field.
• Experience with 3D spatial cameras and Gaussian Splat techniques.
• Proficiency in Python; knowledge of C++ and CUDA is desirable.

Responsibilities

• Develop 3D visualisation tools for accessible rail station walkthroughs.
• Apply ML models for object detection and scene segmentation.
• Integrate conversational AI for location-aware recommendations.
• Collaborate with Railscape and university teams; present at conferences.
• Publish academic papers and patent applications.

Skills

3D visualization

Python

C++

CUDA

Deep learning

Machine learning

AI

Education

Master’s degree in AI

Tools

Gaussian Splat

LiDAR

SLAM

Job description

Knowledge Transfer Partnerships (KTPs) are a unique UK-wide activity that help businesses to improve their competitiveness and productivity by making better use of the knowledge, technology and skills within universities, colleges and research organisations.

Further information is available at: https://iuk-ktp.org.uk/

THE PROJECT

The University of Essex in partnership with Railscape Limited offers an exciting opportunity to a graduate with the relevant skills and knowledge to develop an intelligent 3D visualisation platform that provides personalised, accessibility-aware 3D walkthroughs of rail stations and other major infrastructure sites using advanced spatial computing and AI.

DUTIES OF THE POST

The duties of the post will include:

• Using 3D spatial cameras for modelling railway station infrastructures / facilities to visualise passenger routes and identify objects, assets and areas posing accessibility issues for customers.
• Develop digital 3D mapping tools for capturing passenger routes based on captured video, dense point cloud, spatial and localisation data/processes for generating interactive 3D video guides / walkthrough of railway stations
• Develop and optimise realistic 3D Gaussian Splat models of railway stations / assets from captured 2D photos and videos, ensuring visual quality, spatial accuracy, performance across diverse computationally constraint hardware platforms and interfaces
• Apply state of the art machine learning models for object detection, scene segmentation with the integration of sensor data on operational / usage patterns to identify accessibility issues and risks to customers
• Integrate conversational AI into assistive digital applications for generating personalised, location aware interactive immersive visual walk throughs and accessible route suggestions based on customers’ needs and circumstances.
• Building 3D visualisations for augmented / virtual reality-based interfaces
• Working both independently and as part of a team as both a project manager and a lead researcher
• Balancing innovation with practical implementation
• Working collaboratively with operational staff, senior management, software teams and external rail stakeholders
• Embedding technology and upskilling company staff
• Participating in academic and/or industrial conferences and other events to disseminate research outcomes
• Preparation of academic papers and patent applications

KEY REQUIREMENTS

• A minimum of a Master’s degree in AI, Computer Science Robotics, Mechatronics or Electronic Engineering (Essential)
• Practical and theoretical knowledge of integrating 3D spatial camera features (Gaussian Splat, LiDAR / rendered point cloud data, SLAM, geospatial data) for generating interactive 3D visual scenes
• Practical and theoretical knowledge of advanced deep learning approaches applied to computer vision and multimodal data processing
• Knowledge and experience of developing generative AI applications
• Experience of applying data fusion and machine learning techniques to data rich problems
• A high level of ability in the use of Python
• Additional experience with C++ (desirable)
• Additional experience with CUDA / GPU optimisation (desirable)
• Experience of mobile / web application design and development
• Excellent communication skills and the ability to convey ideas and concepts to a variety of key stakeholders
• The ability to act as both a project manager and a lead researcher
• The ability to work both independently and as part of a team

LOCATION

Railscape Limited, 15 Totman Crescent, Rayleigh, Essex, SS6 7UY

Our website http://www.essex.ac.uk contains more information about the University of Essex. If you have a disability & would like information in a different format, please email .